Advertisement

Electrical and Physical Sensors for Biomedical Implants

  • P. Kassanos
  • S. Anastasova
  • Guang-Zhong Yang
Chapter

Abstract

In addition to the electrochemical sensors discussed in Chap.  2, a range of other sensing modalities are also important for biomedical and implantable applications. The frequency-dependent electrical properties of tissues are essential for assessing various physiological parameters. This, for example, can be quantified via electrical bioimpedance measurements, which can be combined and corroborated with electrochemical sensors. The human body is a dynamic system in constant motion; therefore, sensors for the measurement of physical properties such as strain and pressure are also important. Sensors for these applications rely on the measurement of resistance, capacitance, and sometimes inductance, and these will also be discussed in this chapter for completeness. Temperature is an important health marker for various applications, and consequently the current state of the art in temperature sensors is also discussed, in terms of both monolithic integration and discrete sensor solutions. Monitoring of the electrical response of the nervous system and the delivery of stimuli represent an important family of applications for neuroscience research and neuroprosthetic devices. These will be addressed in this chapter, along with various application scenarios. Other aspects to be discussed include sensor metrics, such as sensitivity, limit of detection, stability, linear range, selectivity, and specificity.

List of Acronyms

AA

Ascorbic acid

AC

Alternating current

AM

Amplitude modulation

AMR

Anisotropic magnetoresistance

ASIC

Application specific integrated circuit

ATP

Adenosine triphosphate

BGA

Ball grid array

BJT

Bipolar junction transistor

BPF

Bandpass filter

CF

Crest factor

CIN

Cervical intraepithelial neoplasia

CM

Conformal mapping

CNT

Carbon nanotube

CMOS

Complementary metal-oxide semiconductor

CMRR

Common-mode rejection ratio

CTAT

Complementary to absolute temperature

CVD

Cardiovascular disease

DAC

Digital-to-analog converter

DBS

Deep brain stimulation

DC

Direct current

DDS

Direct digital synthesis

DIBS

Discrete interval binary sequence

EIS

Electrical impedance spectroscopy

EIT

Electrical impedance tomography

EVD

External ventricular drain

FEM

Finite element method

FET

Field-effect transistor

FFT

Fast Fourier transform

FOG

Freezing of gait

FPGA

Field programmable gate arrays

GF

Gauge factor

GI

Gastro-intestinal

GMR

Giant magnetoresistance

GOD

Glucose oxidase

HEX

Hexokinase

HPF

High-pass filter

I

In-phase

ICP

Intracranial pressure

IOP

Intraocular pressure

ISE

Ion selective electrode

ISFET

Ion-sensitive field-effect transistor

LOD

Limit of detection

LPF

Low-pass filter

MEG

Magneto-encephalography

MEMS

Micro-electro-mechanical systems

MLBS

Maximum length binary sequence

MOSFET

Metal-oxide-semiconductor field-effect transistor

MWCNT

Multi-walled carbon nanotube

MP

Magnitude/phase

NMRR

Normal mode rejection ratio

NTC

Negative temperature coefficient

OTA

Operational transconductance amplifier

PAC

Patient auxiliary currents

PCB

Printed circuit board

PDMS

Polydimethylsiloxane

PEN

Poly (ethylene naphthalate)

PET

Polyethylene terephthalate

PI

Polyimide

PSA

Prostate specific antigen

PTAT

Proportional to absolute temperature

Q

Quadrature

RE

Reference electrode

RF

Radio frequency

RMS

Root mean square

RRF

Resonance response frequency

RTD

Resistance temperature detector

SAW

Surface acoustic wave

SD

Synchronous demodulation

SEM

Scanning electron microscope

SMRR

Series mode rejection ratio

SNR

Signal to noise ratio

SOI

Silicon-on-insulator

SQUID

Superconducting quantum interference devices

SO

Sphincter of Oddi

SOM

Sphincter of Oddi manometry

SRR

Split ring resonator

SS

Synchronous sampling

ssDNA

Single stranded deoxyribonucleic acid

SSI

Surgical site infection

SWCNT

Single-walled carbon nanotube

TCR

Temperature coefficient of resistance

TRUS

Transrectal ultrasound

UA

Uric acid

VCCS

Voltage controlled current source

VOR

Vestibulo-ocular reflex

ZOH

Zero-order hold

References

  1. 1.
    F. Lisdat, D. Schäfer, The use of electrochemical impedance spectroscopy for biosensing. Anal. Bioanal. Chem. 391(5), 1555–1567 (2008)CrossRefGoogle Scholar
  2. 2.
    P. Kassanos, I.F. Triantis, A CMOS multi-sine signal generator for multi-frequency bioimpedance measurements, in 2014 IEEE International Symposium on Circuits and Systems (ISCAS), (2014), pp. 249–252Google Scholar
  3. 3.
    W.R.B. Lionheart, J. Kaipio, C.N. McLeod, Generalized optimal current patterns and electrical safety in EIT. Physiol. Meas. 22(1), 85–90 (2001)CrossRefGoogle Scholar
  4. 4.
    S. Grimnes, O.G. Martinsen, Bioimpedance and Bioelectricity Basics, 1st edn. (Academic Press, Suffolk, UK, 2000)Google Scholar
  5. 5.
    C. Gabriel, S. Gabriel, E. Corthout, The dielectric properties of biological tissues: I. Literature survey. Phys. Med. Biol. 41(11), 2231–2249 (1996)CrossRefGoogle Scholar
  6. 6.
    O.G. Martinsen, S. Grimnes, H.P. Schwan, “Interface phenomena and dielectric properties of biological tissue”, in Encyclopedia of Surface and Colloid Science (Marcel Dekker, New York, 2002), pp. 2643–2652Google Scholar
  7. 7.
    H.P. Schwan, Electrical properties of body tissues and impedance plethysmography. IRE Trans. Med. Electron. PGME 3, 32–46 (1955)CrossRefGoogle Scholar
  8. 8.
    M. Min, T. Parve, A. Ronk, P. Annus, T. Paavle, Synchronous sampling and demodulation in an instrument for multifrequency bioimpedance measurement. IEEE Trans. Instrum. Meas. 56(4), 1365–1372 (2007)CrossRefGoogle Scholar
  9. 9.
    C.L. del Rio et al., Early time course of myocardial electrical impedance during acute coronary artery occlusion in pigs, dogs, and humans. J. Appl. Physiol. 99(4), 1576–1581 (2005)CrossRefGoogle Scholar
  10. 10.
    A. McEwan, J. Tapson, A. van Schaik, D.S. Holder, Code-division-multiplexed electrical impedance tomography spectroscopy. IEEE Trans. Biomed. Circuits Syst. 3(5), 332–338 (2009)CrossRefGoogle Scholar
  11. 11.
    S. Abdul, B.H. Brown, P. Milnes, J.A. Tidy, The use of electrical impedance spectroscopy in the detection of cervical intraepithelial neoplasia. Int. J. Gynecol. Cancer 16(5), 1823–1832 (2006)CrossRefGoogle Scholar
  12. 12.
    H.-G. Jahnke et al., Impedance spectroscopy—an outstanding method for label-free and real-time discrimination between brain and tumor tissue in vivo. Biosens. Bioelectron. 46, 8–14 (2013)CrossRefGoogle Scholar
  13. 13.
    Y. Wan, R. Halter, A. Borsic, P. Manwaring, A. Hartov, K. Paulsen, Sensitivity study of an ultrasound coupled transrectal electrical impedance tomography system for prostate imaging. Physiol. Meas. 31(8), S17–S29 (2010)CrossRefGoogle Scholar
  14. 14.
    J. Harms, A. Schneider, M. Baumgartner, J. Henke, R. Busch, Diagnosing acute liver graft rejection: experimental application of an implantable telemetric impedance device in native and transplanted porcine livers. Biosens. Bioelectron. 16(3), 169–177 (2001)CrossRefGoogle Scholar
  15. 15.
    C.A. González-Correa et al., Virtual biopsies in Barrett’s esophagus using an impedance probe. Ann. N. Y. Acad. Sci. 873(1), 313–321 (1999)CrossRefGoogle Scholar
  16. 16.
    H.N. Nguyen, J. Silny, S. Matern, Multiple intraluminal electrical impedancometry for recording of upper gastrointestinal motility: current results and further implications. Am. J. Gastroenterol. 94(2), 306–317 (1999)CrossRefGoogle Scholar
  17. 17.
    A.J. Bredenoord, B.L.A.M. Weusten, D. Sifrim, R. Timmer, A.J.P.M. Smout, Aerophagia, gastric, and supragastric belching: a study using intraluminal electrical impedance monitoring. Gut 53(11), 1561–1565 (2004)CrossRefGoogle Scholar
  18. 18.
    C.A. González, C. Villanueva, S. Othman, R. Narváez, E. Sacristán, Impedance spectroscopy for monitoring ischemic injury in the intestinal mucosa. Physiol. Meas. 24(2), 277–289 (2003)CrossRefGoogle Scholar
  19. 19.
    H. Imam, C. Sanmiguel, B. Larive, Y. Bhat, E. Soffer, Study of intestinal flow by combined videofluoroscopy, manometry, and multiple intraluminal impedance. Am. J. Physiol. Gastrointest. Liver Physiol. 286(2), G263–G270 (2004)CrossRefGoogle Scholar
  20. 20.
    J.L. Gonzalez-Guillaumin, D.C. Sadowski, O. Yadid-Pecht, K.V.I.S. Kaler, M.P. Mintchev, Multichannel pressure, bolus transit, and pH esophageal catheter. IEEE Sens. J. 6(3), 796–803 (2006)CrossRefGoogle Scholar
  21. 21.
    A.J. Bredenoord, B.L.A.M. Weusten, R. Timmer, A.J.P.M. Smout, Minimum sample frequency for multichannel intraluminal impedance measurement of the oesophagus. Neurogastroenterol. Motil. 16(6), 713–719 (2004)CrossRefGoogle Scholar
  22. 22.
    A. Al-Zaben, V. Chandrasekar, Computation of intraluminal impedance. Physiol. Meas. 25(1), 61 (2004)CrossRefGoogle Scholar
  23. 23.
    J. Fass et al., Measuring esophageal motility with a new intraluminal impedance device: first clinical results in reflux patients. Scand. J. Gastroenterol. 29(8), 693–702 (1994)CrossRefGoogle Scholar
  24. 24.
    R. Tutuian, M.F. Vela, S.S. Shay, D.O. Castell, Multichannel intraluminal impedance in esophageal function testing and gastroesophageal reflux monitoring. J. Clin. Gastroenterol. 37(3), 206–215 (2003)CrossRefGoogle Scholar
  25. 25.
    F. Mellert et al., Detection of (reversible) myocardial ischemic injury by means of electrical bioimpedance. IEEE Trans. Biomed. Eng. 58(6), 1511–1518 (2011)CrossRefGoogle Scholar
  26. 26.
    J. Wtorek et al., Monitoring of myocardium state during off-pump coronary artery by-pass grafting. Physiol. Meas. 29(6), S393–S405 (2008)CrossRefGoogle Scholar
  27. 27.
    Y. Salazar, R. Bragos, O. Casas, J. Cinca, J. Rosell, Transmural versus nontransmural in situ electrical impedance spectrum for healthy, ischemic, and healed myocardium. IEEE Trans. Biomed. Eng. 51(8), 1421–1427 (2004)CrossRefGoogle Scholar
  28. 28.
    R. Dzwonczyk, C. del Rio, D.A. Brown, R.E. Michler, R.K. Wolf, M.B. Howie, Myocardial electrical impedance responds to ischemia and reperfusion in humans. IEEE Trans. Biomed. Eng. 51(12), 2206–2209 (2004)CrossRefGoogle Scholar
  29. 29.
    S. Kun, B. Ristic, R.A. Peura, R.M. Dunn, Algorithm for tissue ischemia estimation based on electrical impedance spectroscopy. IEEE Trans. Biomed. Eng. 50(12), 1352–1359 (2003)CrossRefGoogle Scholar
  30. 30.
    B. Ristic, S. Kun, R.A. Peura, Muscle tissue ischemia monitoring using impedance spectroscopy: quantitative results of animal studies, in Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, (1997), pp. 2108–2111Google Scholar
  31. 31.
    O. Casas et al., In vivo and in situ ischemic tissue characterization using electrical impedance spectroscopya. Ann. N. Y. Acad. Sci. 873(1), 51–58 (1999)CrossRefGoogle Scholar
  32. 32.
    M.A. Fallert et al., Myocardial electrical impedance mapping of ischemic sheep hearts and healing aneurysms. Circulation 87(1), 199–207 (1993)CrossRefGoogle Scholar
  33. 33.
    A. Ivorra et al., Minimally invasive silicon probe for electrical impedance measurements in small animals. Biosens. Bioelectron. 19(4), 391–399 (2003)MathSciNetCrossRefGoogle Scholar
  34. 34.
    R. Gómez et al., A SiC microdevice for the minimally invasive monitoring of ischemia in living tissues. Biomed. Microdevices 8(1), 43–49 (2006)CrossRefGoogle Scholar
  35. 35.
    A. Sola et al., Multiparametric monitoring of ischemia-reperfusion in rat kidney: effect of ischemic preconditioning. Transplantation 75(6), 744–749 (2003)CrossRefGoogle Scholar
  36. 36.
    M. Tijero et al., SU-8 microprobe with microelectrodes for monitoring electrical impedance in living tissues. Biosens. Bioelectron. 24(8), 2410–2416 (2009)CrossRefGoogle Scholar
  37. 37.
    J. Cinca et al., Changes in myocardial electrical impedance in human heart graft rejection. Eur. J. Heart Fail. 10(6), 594–600 (2008)CrossRefGoogle Scholar
  38. 38.
    M. Schäfer, C. Schlegel, H.-J. Kirlum, E. Gersing, M.M. Gebhard, Monitoring of damage to skeletal muscle tissues caused by ischemia. Bioelectrochem. Bioenerg. 45(2), 151–155 (1998)CrossRefGoogle Scholar
  39. 39.
    A. Yufera, A. Rueda, J.M. Munoz, R. Doldan, G. Leger, E.O. Rodriguez-Villegas, A tissue impedance measurement chip for myocardial ischemia detection. IEEE Trans. Circuits Syst. Regul. Pap. 52(12), 2620–2628 (2005)CrossRefGoogle Scholar
  40. 40.
    J. Wtorek, L. Jozefiak, A. Polinski, J. Siebert, An averaging two-electrode probe for monitoring changes in myocardial conductivity evoked by ischemia. IEEE Trans. Biomed. Eng. 49(3), 240–246 (2002)CrossRefGoogle Scholar
  41. 41.
    E. Marzec, K. Wachal, The electrical properties of leg skin in normal individuals and in patients with ischemia. Bioelectrochem. Bioenerg. 49(1), 73–75 (1999)CrossRefGoogle Scholar
  42. 42.
    S. Kun, R.A. Peura, Tissue ischemia detection using impedance spectroscopy, in Proceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1994. Engineering Advances: New Opportunities for Biomedical Engineers, (1994), pp. 868–869Google Scholar
  43. 43.
    T. Süselbeck et al., In vivo intravascular electric impedance spectroscopy using a new catheter with integrated microelectrodes. Basic Res. Cardiol. 100(1), 28–34 (2004)CrossRefGoogle Scholar
  44. 44.
    P. Kassanos, R.K. Iles, R.H. Bayford, A. Demosthenous, Towards the development of an electrochemical biosensor for hCGβ detection. Physiol. Meas. 29(6), S241–S254 (2008)CrossRefGoogle Scholar
  45. 45.
    F. Segura-Quijano, J. Sacristán-Riquelme, J. García-Cantón, M.T. Osés, A. Baldi, Towards fully integrated wireless impedimetric sensors. Sensors 10(4), 4071–4082 (2010)CrossRefGoogle Scholar
  46. 46.
    A. Radu et al., Diagnostic of functionality of polymer membrane—based ion selective electrodes by impedance spectroscopy. Anal. Methods 2(10), 1490–1498 (2010)CrossRefGoogle Scholar
  47. 47.
    P. Kassanos, A. Demosthenous, R.H. Bayford, Towards an optimized design for tetrapolar affinity-based impedimetric immunosensors for lab-on-a-chip applications, in IEEE Biomedical Circuits and Systems Conference, 2008. BioCAS, (2008), pp. 141–144Google Scholar
  48. 48.
    P. Kassanos, A. Demosthenous, R.H. Bayford, Comparison of tetrapolar injection-measurement techniques for coplanar affinity-based impedimetric immunosensors, in IEEE Biomedical Circuits and Systems Conference, 2008. BioCAS, (2008), pp. 317–320Google Scholar
  49. 49.
    P. Kassanos, A. Demosthenous, R.H. Bayford, Optimization of bipolar and tetrapolar impedance biosensors, in Proceedings of 2010 IEEE International Symposium on Circuits and Systems (ISCAS), (2010), pp. 1512–1515Google Scholar
  50. 50.
    P. Kassanos, H.M.D. Ip, G.-Z. Yang, A tetrapolar bio-impedance sensing system for gastrointestinal tract monitoring, in 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN), (2015), pp. 1–6Google Scholar
  51. 51.
    S. Grimnes, Ø.G. Martinsen, Sources of error in tetrapolar impedance measurements on biomaterials and other ionic conductors. J. Phys. Appl. Phys. 40(1), 9–14 (2007)CrossRefGoogle Scholar
  52. 52.
    B.H. Brown, A.J. Wilson, P. Bertemes-Filho, Bipolar and tetrapolar transfer impedance measurements from volume conductor. Electron. Lett. 36(25), 2060–2062 (2000)CrossRefGoogle Scholar
  53. 53.
    M. Genescà et al., Electrical bioimpedance measurement during hypothermic rat kidney preservation for assessing ischemic injury. Biosens. Bioelectron. 20(9), 1866–1871 (2005)CrossRefGoogle Scholar
  54. 54.
    B. Sanchez, G. Vandersteen, R. Bragos, J. Schoukens, Basics of broadband impedance spectroscopy measurements using periodic excitations. Meas. Sci. Technol. 23(10), 105501 (2012)CrossRefGoogle Scholar
  55. 55.
    B. Sanchez, X. Fernandez, S. Reig, R. Bragos, An FPGA-based frequency response analyzer for multisine and stepped sine measurements on stationary and time-varying impedance. Meas. Sci. Technol. 25(1), 015501 (2014)CrossRefGoogle Scholar
  56. 56.
    A.S. Tucker, R.M. Fox, R.J. Sadleir, Biocompatible, high precision, wideband, improved Howland current source with lead-lag compensation. IEEE Trans. Biomed. Circuits Syst. 7(1), 63–70 (2013)CrossRefGoogle Scholar
  57. 57.
    T. Sun, S. Gawad, C. Bernabini, N.G. Green, H. Morgan, Broadband single cell impedance spectroscopy using maximum length sequences: theoretical analysis and practical considerations. Meas. Sci. Technol. 18(9), 2859–2868 (2007)CrossRefGoogle Scholar
  58. 58.
    J. Ojarand, M. Min, P. Annus, Crest factor optimization of the multisine waveform for bioimpedance spectroscopy. Physiol. Meas. 35(6), 1019–1033 (2014)Google Scholar
  59. 59.
    Y. Yang, F. Zhang, K. Tao, B. Sanchez, H. Wen, Z. Teng, An improved crest factor minimization algorithm to synthesize multisines with arbitrary spectrum. Physiol. Meas. 36(5), 895–910 (2015)CrossRefGoogle Scholar
  60. 60.
    F. Seoane, R. Macías, R. Bragós, K. Lindecrantz, Simple voltage-controlled current source for wideband electrical bioimpedance spectroscopy: circuit dependences and limitations. Meas. Sci. Technol. 22(11), 115801 (2011)CrossRefGoogle Scholar
  61. 61.
    P. Bertemes-Filho, B.H. Brown, A.J. Wilson, A comparison of modified Howland circuits as current generators with current mirror type circuits. Physiol. Meas. 21(1), 1–6 (2000)CrossRefGoogle Scholar
  62. 62.
    H. Hong, M. Rahal, A. Demosthenous, R.H. Bayford, Comparison of a new integrated current source with the modified Howland circuit for EIT applications. Physiol. Meas. 30(10), 999–1007 (2009)CrossRefGoogle Scholar
  63. 63.
    A.C. Ivorra, Contributions to the measurement of electrical impedance for living tissue ischemia injury monitoring—OpenThesis, Universitat Politécnica de Catalunya, 2005Google Scholar
  64. 64.
    P. Kassanos, I.F. Triantis, A. Demosthenous, A CMOS magnitude/phase measurement chip for impedance spectroscopy. IEEE Sens. J. 13(6), 2229–2236 (2013)CrossRefGoogle Scholar
  65. 65.
    Y. Yang, J. Wang, G. Yu, F. Niu, P. He, Design and preliminary evaluation of a portable device for the measurement of bioimpedance spectroscopy. Physiol. Meas. 27(12), 1293–1310 (2006)CrossRefGoogle Scholar
  66. 66.
    P. Kassanos, L. Constantinou, I.F. Triantis, A. Demosthenous, An integrated analog readout for multi-frequency bioimpedance measurements. IEEE Sens. J. 14(8), 2792–2800 (2014)CrossRefGoogle Scholar
  67. 67.
    R. Pallás-Areny, J.G. Webster, Analog Signal Processing (Wiley, New York, 1999)Google Scholar
  68. 68.
    R. Gonzalez-Landaeta, O. Casas, R. Pallas-Areny, Heart rate detection from plantar bioimpedance measurements. IEEE Trans. Biomed. Eng. 55(3), 1163–1167 (2008)CrossRefGoogle Scholar
  69. 69.
    R. Pallas-Areny, O. Casas, A novel differential synchronous demodulator for AC signals. IEEE Trans. Instrum. Meas. 45(2), 413–416 (1996)CrossRefGoogle Scholar
  70. 70.
    R. Pallas-Areny, J.G. Webster, Bioelectric impedance measurements using synchronous sampling. IEEE Trans. Biomed. Eng. 40(8), 824–829 (1993)CrossRefGoogle Scholar
  71. 71.
    C. Margo, J. Katrib, M. Nadi, A. Rouane, A four-electrode low frequency impedance spectroscopy measurement system using the AD5933 measurement chip. Physiol. Meas. 34(4), 391–405 (2013)CrossRefGoogle Scholar
  72. 72.
    N. Mehmood, A. Hariz, R. Fitridge, N.H. Voelcker, Applications of modern sensors and wireless technology in effective wound management. J. Biomed. Mater. Res. B Appl. Biomater. 102(4), 885–895 (2014)CrossRefGoogle Scholar
  73. 73.
    R.C. Webb et al., Ultrathin conformal devices for precise and continuous thermal characterization of human skin. Nat. Mater. 12(10), 938–944 (2013)CrossRefGoogle Scholar
  74. 74.
    A.C. Paglinawan, Y.-H. Wang, S.-C. Cheng, C.-C. Chuang, W.-Y. Chung, CMOS temperature sensor with constant power consumption multi-level comparator for implantable bio-medical devices. Electron. Lett. 45(25), 1291–1292 (2009)CrossRefGoogle Scholar
  75. 75.
    L. Xu et al., 3D multifunctional integumentary membranes for spatiotemporal cardiac measurements and stimulation across the entire epicardium. Nat. Commun. 5, 3329 (2014)Google Scholar
  76. 76.
    F. Graichen, G. Bergmann, A. Rohlmann, Hip endoprosthesis for in vivo measurement of joint force and temperature. J. Biomech. 32(10), 1113–1117 (1999)CrossRefGoogle Scholar
  77. 77.
    D.P. Jones, Biomedical Sensors (Momentum Press, New York, 2010)Google Scholar
  78. 78.
    D. Li (ed.) Resistance thermometers, in Encyclopedia of Microfluidics and Nanofluidics (Springer, US, 2008), pp. 1790–1790Google Scholar
  79. 79.
    D.-H. Kim et al., Epidermal electronics. Science 333(6044), 838–843 (2011)CrossRefGoogle Scholar
  80. 80.
    W.-H. Yeo et al., Multifunctional epidermal electronics printed directly onto the skin. Adv. Mater. 25(20), 2773–2778 (2013)CrossRefGoogle Scholar
  81. 81.
    D.-H. Kim et al., Materials for multifunctional balloon catheters with capabilities in cardiac electrophysiological mapping and ablation therapy. Nat. Mater. 10(4), 316–323 (2011)CrossRefGoogle Scholar
  82. 82.
    P.R.N. Childs, J.R. Greenwood, C.A. Long, Review of temperature measurement. Rev. Sci. Instrum. 71(8), 2959–2978 (2000)CrossRefGoogle Scholar
  83. 83.
    A. BaHammam, Comparison of nasal prong pressure and thermistor measurements for detecting respiratory events during sleep. Respiration 71(4), 385–390 (2004)CrossRefGoogle Scholar
  84. 84.
    J. Fei, I. Pavlidis, Thermistor at a distance: unobtrusive measurement of breathing. IEEE Trans. Biomed. Eng. 57(4), 988–998 (2010)CrossRefGoogle Scholar
  85. 85.
    E. Jovanov, D. Raskovic, R. Hormigo, Thermistor-based breathing sensor for circadian rhythm evaluation. Biomed. Sci. Instrum. 37, 493–497 (2001)Google Scholar
  86. 86.
    M.K. Law, A. Bermak, H.C. Luong, A Sub-μW embedded CMOS temperature sensor for RFID food monitoring application. IEEE J. Solid-State Circuits 45(6), 1246–1255 (2010)CrossRefGoogle Scholar
  87. 87.
    M.A.P. Pertijs, G.C.M. Meijer, J.H. Huijsing, Precision temperature measurement using CMOS substrate pnp transistors. IEEE Sens. J. 4(3), 294–300 (2004)CrossRefGoogle Scholar
  88. 88.
    A.L. Aita, M.A.P. Pertijs, K.A.A. Makinwa, J.H. Huijsing, G.C.M. Meijer, Low-power CMOS smart temperature sensor with a batch-calibrated inaccuracy of ±0.25 °C (±3σ) from −70 °C to 130 °C. IEEE Sens. J. 13(5), 1840–1848 (2013)CrossRefGoogle Scholar
  89. 89.
    K. Souri, Y. Chae, K.A.A. Makinwa, A CMOS Temperature Sensor With a Voltage-Calibrated Inaccuracy of 0.15 °C (3) From 55 to 125 °C. IEEE J. Solid-State Circuits 48(1), 292–301 (2013)CrossRefGoogle Scholar
  90. 90.
    K. Ueno, T. Asai, Y. Amemiya, Low-power temperature-to-frequency converter consisting of subthreshold CMOS circuits for integrated smart temperature sensors. Sens. Actuators Phys. 165(1), 132–137 (2011)CrossRefGoogle Scholar
  91. 91.
    C. Azcona, B. Calvo, N. Medrano, S. Celma, CMOS quasi-digital temperature sensor for battery operated systems. Electron. Lett. 49(21), 1338–1340 (2013)CrossRefGoogle Scholar
  92. 92.
    A. Vaz et al., Full passive UHF tag with a temperature sensor suitable for human body temperature monitoring. IEEE Trans. Circuits Syst. II Express Briefs 57(2), 95–99 (2010)CrossRefGoogle Scholar
  93. 93.
    S. Jeong, Z. Foo, Y. Lee, J.-Y. Sim, D. Blaauw, D. Sylvester, A fully-integrated 71 nW CMOS temperature sensor for low power wireless sensor nodes. IEEE J. Solid-State Circuits 49(8), 1682–1693 (2014)CrossRefGoogle Scholar
  94. 94.
    F. Khoshnoud, C.W. de Silva, Recent advances in MEMS sensor technology-biomedical applications. IEEE Instrum. Meas. Mag. 15(1), 8–14 (2012)CrossRefGoogle Scholar
  95. 95.
    F. Khoshnoud, C.W. de Silva, Recent advances in MEMS sensor technology-mechanical applications. IEEE Instrum. Meas. Mag. 15(2), 14–24 (2012)CrossRefGoogle Scholar
  96. 96.
    C.-C. Yang, Y.-L. Hsu, A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors 10(8), 7772–7788 (2010)CrossRefGoogle Scholar
  97. 97.
    Y.J. Huang et al., A CMOS cantilever-based label-free DNA SoC with improved sensitivity for Hepatitis B virus detection. IEEE Trans. Biomed. Circuits Syst. 7(6), 820–831 (2013)CrossRefGoogle Scholar
  98. 98.
    X. Yu, Y. Tang, H. Zhang, T. Li, W. Wang, Design of high-sensitivity cantilever and its monolithic integration with CMOS circuits. IEEE Sens. J. 7(4), 489–495 (2007)CrossRefGoogle Scholar
  99. 99.
    G. Grimaldi, M. Manto, Neurological tremor: sensors, signal processing and emerging applications. Sensors 10(2), 1399–1422 (2010)CrossRefGoogle Scholar
  100. 100.
    S. Patel, H. Park, P. Bonato, L. Chan, M. Rodgers, A review of wearable sensors and systems with application in rehabilitation. J. NeuroEngineering Rehabil. 9, 21 (2012)CrossRefGoogle Scholar
  101. 101.
    H. Chen, M. Xue, Z. Mei, S. Bambang Oetomo, W. Chen, A review of wearable sensor systems for monitoring body movements of neonates. Sensors 16(12), 2134 (2016)CrossRefGoogle Scholar
  102. 102.
    T.G. Constandinou, J. Georgiou, A micropower tilt-processing circuit. IEEE Trans. Biomed. Circuits Syst. 3(6), 363–369 (2009)CrossRefGoogle Scholar
  103. 103.
    H. Zeng, Y. Zhao, Sensing movement: microsensors for body motion measurement. Sensors 11(1), 638–660 (2011)CrossRefGoogle Scholar
  104. 104.
    C.M. Andreou, Y. Pahitas, J. Georgiou, Bio-inspired micro-fluidic angular-rate sensor for vestibular prostheses. Sensors 14(7), 13173–13185 (2014)CrossRefGoogle Scholar
  105. 105.
    S. Kon, R. Horowitz, A high-resolution MEMS piezoelectric strain sensor for structural vibration detection. IEEE Sens. J. 8(12), 2027–2035 (2008)CrossRefGoogle Scholar
  106. 106.
    Y.M. Wang, P.K. Chan, H.K.H. Li, S.E. Ong, A low-power highly sensitive capacitive accelerometer IC using auto-zero time-multiplexed differential technique. IEEE Sens. J. 15(11), 6179–6191 (2015)CrossRefGoogle Scholar
  107. 107.
    G. Langfelder, A.F. Longoni, A. Tocchio, E. Lasalandra, MEMS motion sensors based on the variations of the fringe capacitances. IEEE Sens. J. 11(4), 1069–1077 (2011)CrossRefGoogle Scholar
  108. 108.
    C.M. Sun, M.H. Tsai, Y.C. Liu, W. Fang, Implementation of a monolithic single proof-mass tri-axis accelerometer using CMOS-MEMS technique. IEEE Trans. Electron Devices 57(7), 1670–1679 (2010)CrossRefGoogle Scholar
  109. 109.
    S. Tez, U. Aykutlu, M.M. Torunbalci, T. Akin, A Bulk-micromachined three-axis capacitive MEMS accelerometer on a single die. J. Microelectromechanical Syst. 24(5), 1264–1274 (2015)CrossRefGoogle Scholar
  110. 110.
    M.H. Tsai, Y.C. Liu, W. Fang, A three-axis CMOS-MEMS accelerometer structure with vertically integrated fully differential sensing electrodes. J. Microelectromechanical Syst. 21(6), 1329–1337 (2012)CrossRefGoogle Scholar
  111. 111.
    M.H. Tsai, Y.C. Liu, K.C. Liang, W. Fang, Monolithic CMOS-MEMS pure oxide tri-axis accelerometers for temperature stabilization and performance enhancement. J. Microelectromechanical Syst. 24(6), 1916–1927 (2015)CrossRefGoogle Scholar
  112. 112.
    U. Krishnamoorthy et al., In-plane MEMS-based nano-g accelerometer with sub-wavelength optical resonant sensor. Sens. Actuators Phys. 145–146, 283–290 (2008)CrossRefGoogle Scholar
  113. 113.
    G. Zhanshe, C. Fucheng, L. Boyu, C. Le, L. Chao, S. Ke, Research development of silicon MEMS gyroscopes: a review. Microsyst. Technol. 21(10), 2053–2066 (2015)CrossRefGoogle Scholar
  114. 114.
    S. Dellea, F. Giacci, A.F. Longoni, G. Langfelder, In-Plane and out-of-plane MEMS gyroscopes based on piezoresistive NEMS detection. J. Microelectromechanical Syst. 24(6), 1817–1826 (2015)CrossRefGoogle Scholar
  115. 115.
    S. Sonmezoglu, S.E. Alper, T. Akin, An automatically mode-matched MEMS gyroscope with wide and tunable bandwidth. J. Microelectromechanical Syst. 23(2), 284–297 (2014)CrossRefGoogle Scholar
  116. 116.
    S.E. Alper, Y. Temiz, T. Akin, A compact angular rate sensor system using a fully decoupled silicon-on-glass MEMS gyroscope. J. Microelectromechanical Syst. 17(6), 1418–1429 (2008)CrossRefGoogle Scholar
  117. 117.
    Y. Hui, T. Nan, N.X. Sun, M. Rinaldi, High resolution magnetometer based on a high frequency magnetoelectric MEMS-CMOS oscillator. J. Microelectromechanical Syst. 24(1), 134–143 (2015)CrossRefGoogle Scholar
  118. 118.
    G. Langfelder, C. Buffa, A. Frangi, A. Tocchio, E. Lasalandra, A. Longoni, Z-axis magnetometers for MEMS inertial measurement units using an industrial process. IEEE Trans. Ind. Electron. 60(9), 3983–3990 (2013)CrossRefGoogle Scholar
  119. 119.
    K. Sinha, M. Tabib-Azar, 27 pT silicon nitride MEMS magnetometer for brain imaging. IEEE Sens. J. 16(17), 6551–6558 (2016)CrossRefGoogle Scholar
  120. 120.
    V. Kumar, A. Ramezany, M. Mahdavi, S. Pourkamali, Amplitude modulated Lorentz force MEMS magnetometer with picotesla sensitivity. J. Micromechanics Microengineering 26(10), 105021 (2016)CrossRefGoogle Scholar
  121. 121.
    D. Sheng, S. Li, N. Dural, M.V. Romalis, Subfemtotesla scalar atomic magnetometry using multipass cells. Phys. Rev. Lett. 110(16), 160802 (2013)CrossRefGoogle Scholar
  122. 122.
    P. Minotti, S. Brenna, G. Laghi, A.G. Bonfanti, G. Langfelder, A.L. Lacaita, A Sub–400-nT/sqrt(HZ), 775-uW, multi-loop MEMS magnetometer with integrated readout electronics. J. Microelectromechanical Syst. 24(6), 1938–1950 (2015)CrossRefGoogle Scholar
  123. 123.
    J.L. Tanner, D. Mousadakos, K. Giannakopoulos, E. Skotadis, D. Tsoukalas, High strain sensitivity controlled by the surface density of platinum nanoparticles. Nanotechnology 23(28), 285501 (2012)CrossRefGoogle Scholar
  124. 124.
    M. Borghetti, E. Sardini, M. Serpelloni, Preliminary study of resistive sensors in inkjet technology for force measurements in biomedical applications, in 2014 11th International Multi-Conference on Systems, Signals Devices (SSD), (2014), pp. 1–4Google Scholar
  125. 125.
    V. Correia, C. Caparros, C. Casellas, L. Francesch, J.G. Rocha, S. Lanceros-Mendez, Development of inkjet printed strain sensors. Smart Mater. Struct. 22(10), 105028 (2013)CrossRefGoogle Scholar
  126. 126.
    B. Ando, S. Baglio, All-inkjet printed strain sensors. IEEE Sens. J. 13(12), 4874–4879 (2013)CrossRefGoogle Scholar
  127. 127.
    A. Bessonov, M. Kirikova, S. Haque, I. Gartseev, M.J.A. Bailey, Highly reproducible printable graphite strain gauges for flexible devices. Sens. Actuators Phys. 206, 75–80 (2014)CrossRefGoogle Scholar
  128. 128.
    O. Kanoun et al., Flexible carbon nanotube films for high performance strain sensors. Sensors 14(6), 10042–10071 (2014)CrossRefGoogle Scholar
  129. 129.
    Y. Jia, K. Sun, F.J. Agosto, M.T. Quiñones, Design and characterization of a passive wireless strain sensor. Meas. Sci. Technol. 17(11), 2869–2876 (2006)CrossRefGoogle Scholar
  130. 130.
    K.J. Loh, J.P. Lynch, N.A. Kotov, Inductively coupled nanocomposite wireless strain and pH sensors. Smart Struct. Syst. 4(5), 531–548 (2008)CrossRefGoogle Scholar
  131. 131.
    F. Umbrecht et al., Wireless implantable passive strain sensor: design, fabrication and characterization. J. Micromechanics Microengineering 20(8), 085005 (2010)CrossRefGoogle Scholar
  132. 132.
    E.H. Ledet, D. D’Lima, P. Westerhoff, J.A. Szivek, R.A. Wachs, G. Bergmann, Implantable sensor technology: from research to clinical practice. J. Am. Acad. Orthop. Surg. 20(6), 383–392 (2012)CrossRefGoogle Scholar
  133. 133.
    W. Hasenkamp et al., Design and test of a MEMS strain-sensing device for monitoring artificial knee implants. Biomed. Microdevices 15(5), 831–839 (2013)CrossRefGoogle Scholar
  134. 134.
    F. Graichen, R. Arnold, A. Rohlmann, G. Bergmann, Implantable 9-channel telemetry system for in vivo load measurements with orthopedic implants. IEEE Trans. Biomed. Eng. 54(2), 253–261 (2007)CrossRefGoogle Scholar
  135. 135.
    K.C. McGilvray et al., Implantable microelectromechanical sensors for diagnostic monitoring and post-surgical prediction of bone fracture healing. J. Orthop. Res. 33(10), 1439–1446 (2015)CrossRefGoogle Scholar
  136. 136.
    R. Melik et al., Nested metamaterials for wireless strain sensing. IEEE J. Sel. Top. Quantum Electron. 16(2), 450–458 (2010)CrossRefGoogle Scholar
  137. 137.
    R. Melik, E. Unal, N. Kosku Perkgoz, C. Puttlitz, H.V. Demir, Circular high-Q resonating isotropic strain sensors with large shift of resonance frequency under stress. Sensors 9(12), 9444–9451 (2009)CrossRefGoogle Scholar
  138. 138.
    W. Claes, W. Sansen, R. Puers, A 40-μA/channel compensated 18-channel strain gauge measurement system for stress monitoring in dental implants. IEEE J. Solid-State Circuits 37(3), 293–301 (2002)CrossRefGoogle Scholar
  139. 139.
    W. Claes, R. Puers, W. Sansen, M.D. Cooman, J. Duyck, I. Naert, A low power miniaturized autonomous data logger for dental implants. Sens. Actuators Phys. 97–98, 548–556 (2002)CrossRefGoogle Scholar
  140. 140.
    G.Y. Yang, G. Johnson, W.C. Tang, J.H. Keyak, Parylene-based strain sensors for bone. IEEE Sens. J. 7(12), 1693–1697 (2007)CrossRefGoogle Scholar
  141. 141.
    C.P. Geffre, P.R. Finkbone, C.L. Bliss, D.S. Margolis, J.A. Szivek, Load measurement accuracy from sensate scaffolds with and without a cartilage surface. J. Investig. Surg. Off. J. Acad. Surg. Res. 23(3), 156–162 (2010)CrossRefGoogle Scholar
  142. 142.
    E.L. Tan, B.D. Pereles, B. Horton, R. Shao, M. Zourob, K.G. Ong, Implantable biosensors for real-time strain and pressure monitoring. Sensors 8(10), 6396–6406 (2008)CrossRefGoogle Scholar
  143. 143.
    L. Yu, B.J. Kim, E. Meng, Chronically implanted pressure sensors: challenges and state of the field. Sensors 14(11), 20620–20644 (2014)CrossRefGoogle Scholar
  144. 144.
    P.R. Pfau et al., Sphincter of Oddi manometry. Gastrointest. Endosc. 74(6), 1175–1180 (2011)CrossRefGoogle Scholar
  145. 145.
    R. Tan et al., Development of a fully implantable wireless pressure monitoring system. Biomed. Microdevices 11(1), 259–264 (2008)CrossRefGoogle Scholar
  146. 146.
    J. Melgaard, N.J.M. Rijkhoff, Detecting the onset of urinary bladder contractions using an implantable pressure sensor. IEEE Trans. Neural Syst. Rehabil. Eng. 19(6), 700–708 (2011)CrossRefGoogle Scholar
  147. 147.
    P. Bingger, M. Zens, P. Woias, Highly flexible capacitive strain gauge for continuous long-term blood pressure monitoring. Biomed. Microdevices 14(3), 573–581 (2012)CrossRefGoogle Scholar
  148. 148.
    “St. Jude Medical CardioMEMSTM HF System.” [Online]. Available: http://www.sjm.com/cardiomems
  149. 149.
    “St. Jude Medical CardioMEMS HF System Prompts Changes That Improve Heart Failure Management and Reduce Hospitalizations | Business Wire,” 04-Apr–2016. [Online]. Available: http://www.businesswire.com/news/home/20160404005737/en/St.-Jude-Medical-CardioMEMS-HF-System-Prompts. Accessed 07 Feb 2017
  150. 150.
    “Merit Sensor BP SERIES.” [Online]. Available: https://meritsensor.com/products/bp-series/. Accessed 28 Jan 2016
  151. 151.
    K.-H. Shin, C.-R. Moon, T.-H. Lee, C.-H. Lim, Y.-J. Kim, Flexible wireless pressure sensor module. Sens. Actuators Phys. 123–124, 30–35 (2005)CrossRefGoogle Scholar
  152. 152.
    P. Cong, N. Chaimanonart, W.H. Ko, D.J. Young, A wireless and batteryless 10-bit implantable blood pressure sensing microsystem with adaptive RF powering for real-time laboratory mice monitoring. IEEE J. Solid-State Circuits 44(12), 3631–3644 (2009)CrossRefGoogle Scholar
  153. 153.
    N.J. Cleven et al., A novel fully implantable wireless sensor system for monitoring hypertension patients. IEEE Trans. Biomed. Eng. 59(11), 3124–3130 (2012)CrossRefGoogle Scholar
  154. 154.
    O.H. Murphy et al., Continuous in vivo blood pressure measurements using a fully implantable wireless SAW sensor. Biomed. Microdevices 15(5), 737–749 (2013)CrossRefGoogle Scholar
  155. 155.
    C.-C. Chiang, C.-C.K. Lin, M.-S. Ju, An implantable capacitive pressure sensor for biomedical applications. Sens. Actuators Phys. 134(2), 382–388 (2007)CrossRefGoogle Scholar
  156. 156.
    M.K. Filippidou, E. Tegou, V. Tsouti, S. Chatzandroulis, A flexible strain sensor made of graphene nanoplatelets/polydimethylsiloxane nanocomposite. Microelectron. Eng. 142, 7–11 (2015)CrossRefGoogle Scholar
  157. 157.
    K.G. Ong, C.A. Grimes, A resonant printed-circuit sensor for remote query monitoring of environmental parameters. Smart Mater. Struct. 9(4), 421–428 (2000)CrossRefGoogle Scholar
  158. 158.
    J.C.-H. Lin, Y. Zhao, P.-J. Chen, M. Humayun, Y.-C. Tai, Feeling the pressure: a parylene-based intraocular pressure sensor. IEEE Nanotechnol. Mag. 6(3), 8–16 (2012)CrossRefGoogle Scholar
  159. 159.
    P.-J. Chen, D.C. Rodger, S. Saati, M.S. Humayun, Y.-C. Tai, Microfabricated implantable parylene-based wireless passive intraocular pressure sensors. J. Microelectromechanical Syst. 17(6), 1342–1351 (2008)CrossRefGoogle Scholar
  160. 160.
    P.-J. Chen, S. Saati, R. Varma, M.S. Humayun, Y.-C. Tai, Wireless intraocular pressure sensing using microfabricated minimally invasive flexible-coiled LC sensor implant. J. Microelectromechanical Syst. 19(4), 721–734 (2010)CrossRefGoogle Scholar
  161. 161.
    P.K. Eide, A. Bakken, The baseline pressure of intracranial pressure (ICP) sensors can be altered by electrostatic discharges. Biomed. Eng. OnLine 10(1), 75 (2011)CrossRefGoogle Scholar
  162. 162.
    “Codman Neuro ICP EXPRESS® Monitoring System.” [Online]. Available: https://www.depuysynthes.com/hcp/codman-neuro/products/qs/ICP-EXPRESS-Monitoring-System. Accessed 28 Jan 2016
  163. 163.
  164. 164.
    “Integra Camino Intracranial Pressure Monitor Brochure.”Google Scholar
  165. 165.
    “Integra Camino Intracranial Pressure Monitoring Kit Brochure.”Google Scholar
  166. 166.
    S.F. Cogan, Neural stimulation and recording electrodes. Annu. Rev. Biomed. Eng. 10(1), 275–309 (2008)CrossRefGoogle Scholar
  167. 167.
    D.J. Edell, V.V. Toi, V.M. McNeil, L.D. Clark, Factors influencing the biocompatibility of insertable silicon microshafts in cerebral cortex. IEEE Trans. Biomed. Eng. 39(6), 635–643 (1992)CrossRefGoogle Scholar
  168. 168.
    D.H. Szarowski et al., Brain responses to micro-machined silicon devices. Brain Res. 983(1–2), 23–35 (2003)CrossRefGoogle Scholar
  169. 169.
    R. Biran, D.C. Martin, P.A. Tresco, Neuronal cell loss accompanies the brain tissue response to chronically implanted silicon microelectrode arrays. Exp. Neurol. 195(1), 115–126 (2005)CrossRefGoogle Scholar
  170. 170.
    J.K. Niparko, R.A. Altschuler, J.A. Wiler, X. Xue, D.J. Anderson, Surgical implantation and biocompatibility of central nervous system auditory prostheses. Ann. Otol. Rhinol. Laryngol. 98(12), 965–970 (1989)CrossRefGoogle Scholar
  171. 171.
    Y.-T. Kim, R.W. Hitchcock, M.J. Bridge, P.A. Tresco, Chronic response of adult rat brain tissue to implants anchored to the skull. Biomaterials 25(12), 2229–2237 (2004)CrossRefGoogle Scholar
  172. 172.
    M.B.A. Fontes, Electrodes for bio-application: recording and stimulation. J. Phys: Conf. Ser. 421(1), 012019 (2013)Google Scholar
  173. 173.
    A.R. Harris, S.J. Morgan, J. Chen, R.M.I. Kapsa, G.G. Wallace, A.G. Paolini, Conducting polymer coated neural recording electrodes. J. Neural Eng. 10(1), 016004 (2013)CrossRefGoogle Scholar
  174. 174.
    F. Vitale, S.R. Summerson, B. Aazhang, C. Kemere, M. Pasquali, Neural stimulation and recording with bidirectional, soft carbon nanotube fiber microelectrodes. ACS Nano 9(4), 4465–4474 (2015)CrossRefGoogle Scholar
  175. 175.
    Z. Lertmanorat, F.W. Montague, D.M. Durand, A flat interface nerve electrode with integrated multiplexer. IEEE Trans. Neural Syst. Rehabil. Eng. 17(2), 176–182 (2009)CrossRefGoogle Scholar
  176. 176.
    K. Najafi, Solid-state microsensors for cortical nerve recordings. IEEE Eng. Med. Biol. Mag. 13(3), 375–387 (1994)CrossRefGoogle Scholar
  177. 177.
    C.G. Herrera, A.R. Adamantidis, An integrated microprobe for the brain. Nat. Biotechnol. 33(3), 259–260 (2015)CrossRefGoogle Scholar
  178. 178.
    A.N. van den Pol, Neuropeptide transmission in brain circuits. Neuron 76(1), 98–115 (2012)CrossRefGoogle Scholar
  179. 179.
    A. Canales et al., Multifunctional fibers for simultaneous optical, electrical and chemical interrogation of neural circuits in vivo. Nat. Biotechnol. 33(3), 277–284 (2015)CrossRefGoogle Scholar
  180. 180.
    P. Fattahi, G. Yang, G. Kim, M.R. Abidian, A review of organic and inorganic biomaterials for neural interfaces. Adv. Mater. 26(12), 1846–1885 (2014)CrossRefGoogle Scholar
  181. 181.
    M.R. Abidian, D.C. Martin, Experimental and theoretical characterization of implantable neural microelectrodes modified with conducting polymer nanotubes. Biomaterials 29(9), 1273–1283 (2008)CrossRefGoogle Scholar
  182. 182.
    X. Cui, D.C. Martin, Electrochemical deposition and characterization of poly(3,4-ethylenedioxythiophene) on neural microelectrode arrays. Sens. Actuators B Chem. 89(1–2), 92–102 (2003)CrossRefGoogle Scholar
  183. 183.
    L.R. Hochberg et al., Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442(7099), 164–171 (2006)CrossRefGoogle Scholar
  184. 184.
    S. Negi, R. Bhandari, L. Rieth, R. Van Wagenen, F. Solzbacher, Neural electrode degradation from continuous electrical stimulation: comparison of sputtered and activated iridium oxide. J. Neurosci. Methods 186(1), 8–17 (2010)CrossRefGoogle Scholar
  185. 185.
    A. Goryu, R. Numano, A. Ikedo, M. Ishida, T. Kawano, Nanoscale tipped microwire arrays enhance electrical trap and depth injection of nanoparticles. Nanotechnology 23(41), 415301 (2012)CrossRefGoogle Scholar
  186. 186.
    T. Stieglitz, Development of a micromachined epiretinal vision prosthesis. J. Neural Eng. 6(6), 065005 (2009)CrossRefGoogle Scholar
  187. 187.
    D.C. Rodger et al., Flexible parylene-based multielectrode array technology for high-density neural stimulation and recording. Sens. Actuators B Chem. 132(2), 449–460 (2008)CrossRefGoogle Scholar
  188. 188.
    B. Rubehn, C. Bosman, R. Oostenveld, P. Fries, T. Stieglitz, A MEMS-based flexible multichannel ECoG-electrode array. J. Neural Eng. 6(3), 036003 (2009)CrossRefGoogle Scholar
  189. 189.
    D.-H. Kim et al., Dissolvable films of silk fibroin for ultrathin conformal bio-integrated electronics. Nat. Mater. 9(6), 511–517 (2010)CrossRefGoogle Scholar
  190. 190.
    S.P. Lacour et al., Flexible and stretchable micro-electrodes for in vitro and in vivo neural interfaces. Med. Biol. Eng. Comput. 48(10), 945–954 (2010)CrossRefGoogle Scholar
  191. 191.
    C. Hassler, T. Boretius, T. Stieglitz, Polymers for neural implants. J. Polym. Sci., Part B: Polym. Phys. 49(1), 18–33 (2011)CrossRefGoogle Scholar
  192. 192.
    P. Negredo, J. Castro, N. Lago, X. Navarro, C. Avendaño, Differential growth of axons from sensory and motor neurons through a regenerative electrode: A stereological, retrograde tracer, and functional study in the rat. Neuroscience 128(3), 605–615 (2004)CrossRefGoogle Scholar
  193. 193.
    K.W. Meacham, R.J. Giuly, L. Guo, S. Hochman, S.P. DeWeerth, A lithographically-patterned, elastic multi-electrode array for surface stimulation of the spinal cord. Biomed. Microdevices 10(2), 259–269 (2008)CrossRefGoogle Scholar
  194. 194.
    J.D. MacDonald, K.J. Fisher, Technique for steering spinal cord stimulator electrode. Oper. Neurosurg. 69(1), ons83–ons87 (2011)CrossRefGoogle Scholar
  195. 195.
    X. Kang, J.Q. Liu, H. Tian, B. Yang, Y. Nuli, C. Yang, Self-closed parylene cuff electrode for peripheral nerve recording. J. Microelectromechanical Syst. 24(2), 319–332 (2015)CrossRefGoogle Scholar
  196. 196.
    H. Yu, W. Xiong, H. Zhang, W. Wang, Z. Li, A parylene self-locking cuff electrode for peripheral nerve stimulation and recording. J. Microelectromechanical Syst. 23(5), 1025–1035 (2014)CrossRefGoogle Scholar
  197. 197.
    A. Branner, R.B. Stein, R.A. Normann, Selective stimulation of cat sciatic nerve using an array of varying-length microelectrodes. J. Neurophysiol. 85(4), 1585–1594 (2001)CrossRefGoogle Scholar
  198. 198.
    J. Zariffa, M.K. Nagai, Z.J. Daskalakis, M.R. Popovic, Influence of the number and location of recording contacts on the selectivity of a nerve cuff electrode. IEEE Trans. Neural Syst. Rehabil. Eng. 17(5), 420–427 (2009)CrossRefGoogle Scholar
  199. 199.
    S.M. Lawrence, G.S. Dhillon, K.W. Horch, Fabrication and characteristics of an implantable, polymer-based, intrafascicular electrode. J. Neurosci. Methods 131(1–2), 9–26 (2003)CrossRefGoogle Scholar
  200. 200.
    S.M. Lawrence, G.S. Dhillon, W. Jensen, K. Yoshida, K.W. Horch, Acute peripheral nerve recording Characteristics of polymer-based longitudinal intrafascicular electrodes. IEEE Trans. Neural Syst. Rehabil. Eng. 12(3), 345–348 (2004)CrossRefGoogle Scholar
  201. 201.
    K. Warwick et al., The application of implant technology for cybernetic systems. Arch. Neurol. 60(10), 1369–1373 (2003)CrossRefGoogle Scholar
  202. 202.
    M.T. Alt, E. Fiedler, L. Rudmann, J.S. Ordonez, P. Ruther, T. Stieglitz, Let there be light - optoprobes for neural implants. Proc. IEEE 105(1), 101–138 (2017)CrossRefGoogle Scholar
  203. 203.
    M. HajjHassan, V. Chodavarapu, S. Musallam, NeuroMEMS: neural probe microtechnologies. Sensors 8(10), 6704–6726 (2008)CrossRefGoogle Scholar
  204. 204.
    K.D. Wise, D.J. Anderson, J.F. Hetke, D.R. Kipke, K. Najafi, Wireless implantable microsystems: high-density electronic interfaces to the nervous system. Proc. IEEE 92(1), 76–97 (2004)CrossRefGoogle Scholar
  205. 205.
    E.M. Maynard, C.T. Nordhausen, R.A. Normann, The Utah intracortical electrode array: a recording structure for potential brain-computer interfaces. Electroencephalogr. Clin. Neurophysiol. 102(3), 228–239 (1997)CrossRefGoogle Scholar
  206. 206.
    G.G. Naples, J.T. Mortimer, A. Scheiner, J.D. Sweeney, A spiral nerve cuff electrode for peripheral nerve stimulation. IEEE Trans. Biomed. Eng. 35(11), 905–916 (1988)CrossRefGoogle Scholar
  207. 207.
    J. Viventi et al., Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo. Nat. Neurosci. 14(12), 1599–1605 (2011)CrossRefGoogle Scholar
  208. 208.
    A.B. Schwartz, X.T. Cui, D.J. Weber, D.W. Moran, Brain-controlled interfaces: movement restoration with neural prosthetics. Neuron 52(1), 205–220 (2006)CrossRefGoogle Scholar
  209. 209.
    M. Kindlundh, P. Norlin, U.G. Hofmann, A neural probe process enabling variable electrode configurations. Sens. Actuators B Chem. 102(1), 51–58 (2004)CrossRefGoogle Scholar
  210. 210.
    K.-K. Lee et al., Polyimide-based intracortical neural implant with improved structural stiffness. J. Micromechanics Microengineering 14(1), 32–37 (2004)CrossRefGoogle Scholar
  211. 211.
    P.J. Rousche, D.S. Pellinen, D.P. Pivin, J.C. Williams, R.J. Vetter, D.R. Kipke, Flexible polyimide-based intracortical electrode arrays with bioactive capability. IEEE Trans. Biomed. Eng. 48(3), 361–371 (2001)CrossRefGoogle Scholar
  212. 212.
    A. Mercanzini et al., Demonstration of cortical recording using novel flexible polymer neural probes. Sens. Actuators Phys. 143(1), 90–96 (2008)CrossRefGoogle Scholar
  213. 213.
    A.C. Patil, N.V. Thakor, Implantable neurotechnologies: a review of micro- and nanoelectrodes for neural recording. Med. Biol. Eng. Comput. 54(1), 23–44 (2016)CrossRefGoogle Scholar
  214. 214.
    S. Musallam, M.J. Bak, P.R. Troyk, R.A. Andersen, A floating metal microelectrode array for chronic implantation. J. Neurosci. Methods 160(1), 122–127 (2007)CrossRefGoogle Scholar
  215. 215.
    R.A. Normann, E.M. Maynard, P.J. Rousche, D.J. Warren, A neural interface for a cortical vision prosthesis. Vision. Res. 39(15), 2577–2587 (1999)CrossRefGoogle Scholar
  216. 216.
    A. Jackson, E.E. Fetz, Compact movable microwire array for long-term chronic unit recording in cerebral cortex of primates. J. Neurophysiol. 98(5), 3109–3118 (2007)CrossRefGoogle Scholar
  217. 217.
    G. Lehew, M.A.L. Nicolelis, State-of-the-art microwire array design for chronic neural recordings in behaving animals, in Methods for Neural Ensemble Recordings, Second Edition (CRC Press, Boca Raton, FL, 2007), pp. 1–20Google Scholar
  218. 218.
    D.A. Schwarz et al., Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys. Nat. Methods 11(6), 670–676 (2014)CrossRefGoogle Scholar
  219. 219.
    T.D.Y. Kozai et al., Ultrasmall implantable composite microelectrodes with bioactive surfaces for chronic neural interfaces. Nat. Mater. 11(12), 1065–1073 (2012)CrossRefGoogle Scholar
  220. 220.
    D.R. Kipke, R.J. Vetter, J.C. Williams, J.F. Hetke, Silicon-substrate intracortical microelectrode arrays for long-term recording of neuronal spike activity in cerebral cortex. IEEE Trans. Neural Syst. Rehabil. Eng. 11(2), 151–155 (2003)CrossRefGoogle Scholar
  221. 221.
    P.J. Rousche, R.A. Normann, Chronic recording capability of the Utah intracortical electrode array in cat sensory cortex. J. Neurosci. Methods 82(1), 1–15 (1998)CrossRefGoogle Scholar
  222. 222.
    Å.B. Vallbo, K.-E. Hagbarth, Activity from skin mechanoreceptors recorded percutaneously in awake human subjects. Exp. Neurol. 21(3), 270–289 (1968)CrossRefGoogle Scholar
  223. 223.
    N. Lago, K. Yoshida, K.P. Koch, X. Navarro, Assessment of biocompatibility of chronically implanted polyimide and platinum intrafascicular electrodes. IEEE Trans. Biomed. Eng. 54(2), 281–290 (2007)CrossRefGoogle Scholar
  224. 224.
    T. Boretius et al., A transverse intrafascicular multichannel electrode (TIME) to interface with the peripheral nerve. Biosens. Bioelectron. 26(1), 62–69 (2010)CrossRefGoogle Scholar
  225. 225.
    H.A.C. Wark et al., A new high-density (25 electrodes/mm2) penetrating microelectrode array for recording and stimulating sub-millimeter neuroanatomical structures. J. Neural Eng. 10(4), 045003 (2013)CrossRefGoogle Scholar
  226. 226.
    H. Xu et al., Conductive PPY/PDLLA conduit for peripheral nerve regeneration. Biomaterials 35(1), 225–235 (2014)CrossRefGoogle Scholar
  227. 227.
    P.B. Yoo, D.M. Durand, Selective recording of the canine hypoglossal nerve using a multicontact flat interface nerve electrode. IEEE Trans. Biomed. Eng. 52(8), 1461–1469 (2005)CrossRefGoogle Scholar
  228. 228.
    W.M. Grill, Jr., M.D. Tarler, J.T. Mortimer, Implantable helical spiral cuff electrode, US5505201 A, 09 Apr 1996Google Scholar
  229. 229.
    T. Stieglitz, M. Schuetter, K.P. Koch, Implantable biomedical microsystems for neural prostheses. IEEE Eng. Med. Biol. Mag. 24(5), 58–65 (2005)CrossRefGoogle Scholar
  230. 230.
    G. Márton et al., In vivo measurements with robust silicon-based multielectrode arrays with extreme shaft lengths. IEEE Sens. J. 13(9), 3263–3269 (2013)CrossRefGoogle Scholar
  231. 231.
    K.D. Wise, A.M. Sodagar, Y. Yao, M.N. Gulari, G.E. Perlin, K. Najafi, Microelectrodes, microelectronics, and implantable neural microsystems. Proc. IEEE 96(7), 1184–1202 (2008)CrossRefGoogle Scholar
  232. 232.
    N. Xue et al., Polymeric C-shaped cuff electrode for recording of peripheral nerve signal. Sens. Actuators B Chem. 210, 640–648 (2015)CrossRefGoogle Scholar
  233. 233.
    S.B. Brummer, L.S. Robblee, F.T. Hambrecht, Criteria for selecting electrodes for electrical stimulation: theoretical and practical considerations. Ann. N. Y. Acad. Sci. 405(1), 159–171 (1983)CrossRefGoogle Scholar
  234. 234.
    G.E. Loeb, R.A. Peck, Cuff electrodes for chronic stimulation and recording of peripheral nerve activity. J. Neurosci. Methods 64(1), 95–103 (1996)CrossRefGoogle Scholar
  235. 235.
    K.H. Polasek, H.A. Hoyen, M.W. Keith, D.J. Tyler, Human nerve stimulation thresholds and selectivity using a multi-contact nerve cuff electrode. IEEE Trans. Neural Syst. Rehabil. Eng. 15(1), 76–82 (2007)CrossRefGoogle Scholar
  236. 236.
    M.A. Lebedev, M.A.L. Nicolelis, Brain–machine interfaces: past, present and future. Trends Neurosci. 29(9), 536–546 (2006)CrossRefGoogle Scholar
  237. 237.
    L. Kenney et al., An implantable two channel drop foot stimulator: initial clinical results. Artif. Organs 26(3), 267–270 (2002)CrossRefGoogle Scholar
  238. 238.
    D.J. Tyler, D.M. Durand, A slowly penetrating interfascicular nerve electrode for selective activation of peripheral nerves. IEEE Trans. Rehabil. Eng. 5(1), 51–61 (1997)CrossRefGoogle Scholar
  239. 239.
    A. Kundu, K.R. Harreby, K. Yoshida, T. Boretius, T. Stieglitz, W. Jensen, Stimulation selectivity of the ‘thin-film longitudinal intrafascicular electrode’ (tfLIFE) and the ‘transverse intrafascicular multi-channel electrode’ (TIME) in the large nerve animal model. IEEE Trans. Neural Syst. Rehabil. Eng. 22(2), 400–410 (2014)CrossRefGoogle Scholar
  240. 240.
    S. Raspopovic, M. Capogrosso, S. Micera, A computational model for the stimulation of rat sciatic nerve using a transverse intrafascicular multichannel electrode. IEEE Trans. Neural Syst. Rehabil. Eng. 19(4), 333–344 (2011)CrossRefGoogle Scholar
  241. 241.
    X. Navarro, T.B. Krueger, N. Lago, S. Micera, T. Stieglitz, P. Dario, A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems. J. Peripher. Nerv. Syst. 10(3), 229–258 (2005)CrossRefGoogle Scholar
  242. 242.
    L.A. Geddes, R. Roeder, Criteria for the selection of materials for implanted electrodes. Ann. Biomed. Eng. 31(7), 879–890 (2003)CrossRefGoogle Scholar
  243. 243.
    S.H. Cho, H.M. Lu, L. Cauller, M.I. Romero-Ortega, J.B. Lee, G.A. Hughes, Biocompatible SU-8-based microprobes for recording neural spike signals from regenerated peripheral nerve fibers. IEEE Sens. J. 8(11), 1830–1836 (2008)CrossRefGoogle Scholar
  244. 244.
    S. Takeuchi, D. Ziegler, Y. Yoshida, K. Mabuchi, T. Suzuki, Parylene flexible neural probes integrated with microfluidic channels. Lab Chip 5(5), 519–523 (2005)CrossRefGoogle Scholar
  245. 245.
    S. Takeuchi, T. Suzuki, K. Mabuchi, H. Fujita, 3D flexible multichannel neural probe array. J. Micromechanics Microengineering 14(1), 104–107 (2004)CrossRefGoogle Scholar
  246. 246.
    S.E. Lee et al., A flexible depth probe using liquid crystal polymer. IEEE Trans. Biomed. Eng. 59(7), 2085–2094 (2012)CrossRefGoogle Scholar
  247. 247.
    K. Lee, J. He, R. Clement, S. Massia, B. Kim, Biocompatible benzocyclobutene (BCB)-based neural implants with micro-fluidic channel. Biosens. Bioelectron. 20(2), 404–407 (2004)CrossRefGoogle Scholar
  248. 248.
    P.E.K. Donaldson, Aspects of silicone rubber as an encapsulant for neurological prostheses. Med. Biol. Eng. Comput. 29(1), 34–39 (1991)CrossRefGoogle Scholar
  249. 249.
    N.D. Donaldson, P.E.K. Donaldson, When are actively balanced biphasic (‘Lilly’) stimulating pulses necessary in a neurological prosthesis? I historical background; Pt resting potential; Q studies. Med. Biol. Eng. Comput. 24(1), 41–49 (1986)CrossRefGoogle Scholar
  250. 250.
    J.O. Larsen, M. Thomsen, M. Haugland, T. Sinkjær, Degeneration and regeneration in rabbit peripheral nerve with long-term nerve cuff electrode implant: a stereological study of myelinated and unmyelinated axons. Acta Neuropathol. (Berl.) 96(4), 365–378 (1998)CrossRefGoogle Scholar
  251. 251.
    B. Upshaw, T. Sinkjaer, Digital signal processing algorithms for the detection of afferent nerve activity recorded from cuff electrodes. IEEE Trans. Rehabil. Eng. 6(2), 172–181 (1998)CrossRefGoogle Scholar
  252. 252.
    I.F. Triantis, A. Demosthenous, N. Donaldson, On cuff imbalance and tripolar ENG amplifier configurations. IEEE Trans. Biomed. Eng. 52(2), 314–320 (2005)CrossRefGoogle Scholar
  253. 253.
    A. Demosthenous, J. Taylor, I.F. Triantis, R. Rieger, N. Donaldson, Design of an adaptive interference reduction system for nerve-cuff electrode recording. IEEE Trans. Circuits Syst. Regul. Pap. 51(4), 629–639 (2004)CrossRefGoogle Scholar
  254. 254.
    L.N.S. Andreasen, J.J. Struijk, Signal strength versus cuff length in nerve cuff electrode recordings. IEEE Trans. Biomed. Eng. 49(9), 1045–1050 (2002)CrossRefGoogle Scholar
  255. 255.
    T. Stieglitz, H. Beutel, M. Schuettler, J.-U. Meyer, Micromachined, polyimide-based devices for flexible neural interfaces. Biomed. Microdevices 2(4), 283–294 (2000)CrossRefGoogle Scholar
  256. 256.
    D.T.T. Plachta et al., Blood pressure control with selective vagal nerve stimulation and minimal side effects. J. Neural Eng. 11(3), 036011 (2014)CrossRefGoogle Scholar
  257. 257.
    Z. Xiang et al., Progress of flexible electronics in neural interfacing—a self-adaptive non-invasive neural ribbon electrode for small nerves recording. Adv. Mater. 28(22), 4472–4479 (2016)CrossRefGoogle Scholar
  258. 258.
    E.G.R. Kim et al., 3D silicon neural probe with integrated optical fibers for optogenetic modulation. Lab Chip 15(14), 2939–2949 (2015)CrossRefGoogle Scholar
  259. 259.
    A.B. Kibler, B.G. Jamieson, D.M. Durand, A high aspect ratio microelectrode array for mapping neural activity in vitro. J. Neurosci. Methods 204(2), 296–305 (2012)CrossRefGoogle Scholar
  260. 260.
    Z. Xiang et al., Ultra-thin flexible polyimide neural probe embedded in a dissolvable maltose-coated microneedle. J. Micromechanics Microengineering 24(6), 065015 (2014)CrossRefGoogle Scholar
  261. 261.
    D.-W. Park et al., Graphene-based carbon-layered electrode array technology for neural imaging and optogenetic applications. Nat. Commun. 5, 5258 (2014)CrossRefGoogle Scholar
  262. 262.
    D.J. Tyler, D.M. Durand, Functionally selective peripheral nerve stimulation with a flat interface nerve electrode. IEEE Trans. Neural Syst. Rehabil. Eng. 10(4), 294–303 (2002)CrossRefGoogle Scholar
  263. 263.
    C. Veraart, W.M. Grill, J.T. Mortimer, Selective control of muscle activation with a multipolar nerve cuff electrode. IEEE Trans. Biomed. Eng. 40(7), 640–653 (1993)CrossRefGoogle Scholar
  264. 264.
    D.N. Heo et al., Multifunctional hydrogel coatings on the surface of neural cuff electrode for improving electrode-nerve tissue interfaces. Acta Biomater. 39, 25–33 (2016)CrossRefGoogle Scholar
  265. 265.
    S.J. Park et al., Functional nerve cuff electrode with controllable anti-inflammatory drug loading and release by biodegradable nanofibers and hydrogel deposition. Sens. Actuators B Chem. 215, 133–141 (2015)CrossRefGoogle Scholar
  266. 266.
    J. Seo, J.H. Wee, J.H. Park, P. Park, J.-W. Kim, S.J. Kim, Nerve cuff electrode using embedded magnets and its application to hypoglossal nerve stimulation. J. Neural Eng. 13(6), 066014 (2016)CrossRefGoogle Scholar
  267. 267.
    Y.J. Lee, H.-J. Kim, S.H. Do, J.Y. Kang, S.H. Lee, Characterization of nerve-cuff electrode interface for biocompatible and chronic stimulating application. Sens. Actuators B Chem. 237, 924–934 (2016)CrossRefGoogle Scholar
  268. 268.
    S. Lee et al., Selective stimulation and neural recording on peripheral nerves using flexible split ring electrodes. Sens. Actuators B Chem. 242, 1165–1170 (2017)CrossRefGoogle Scholar
  269. 269.
    S. Nag, N.V. Thakor, Implantable neurotechnologies: electrical stimulation and applications. Med. Biol. Eng. Comput. 54(1), 63–76 (2016)CrossRefGoogle Scholar
  270. 270.
    S. Vaddiraju, I. Tomazos, D.J. Burgess, F.C. Jain, F. Papadimitrakopoulos, Emerging synergy between nanotechnology and implantable biosensors: a review. Biosens. Bioelectron. 25(7), 1553–1565 (2010)CrossRefGoogle Scholar
  271. 271.
    G.S. Wilson, M. Ammam, In vivo biosensors. FEBS J. 274(21), 5452–5461 (2007)CrossRefGoogle Scholar
  272. 272.
    G.S. Wilson, R. Gifford, Biosensors for real-time in vivo measurements. Biosens. Bioelectron. 20(12), 2388–2403 (2005)CrossRefGoogle Scholar
  273. 273.
    H. Cao et al., An implantable, batteryless, and wireless capsule with integrated impedance and pH sensors for gastroesophageal reflux monitoring. IEEE Trans. Biomed. Eng. 59(11), 3131–3139 (2012)CrossRefGoogle Scholar
  274. 274.
    H.-J. Chung et al., Stretchable, multiplexed pH sensors with demonstrations on rabbit and human hearts undergoing ischemia. Adv. Healthc. Mater. 3(1), 59–68 (2014)CrossRefGoogle Scholar
  275. 275.
    E. Lindner et al., In vivo and in vitro testing of microelectronically fabricated planar sensors designed for applications in cardiology. Fresenius J. Anal. Chem. 346(6–9), 584–588 (1993)CrossRefGoogle Scholar
  276. 276.
    V.V. Cosofret, E. Lindner, T.A. Johnson, M.R. Neuman, Planar micro sensors for in vivo myocardial pH measurements. Talanta 41(6), 931–938 (1994)CrossRefGoogle Scholar
  277. 277.
    V.V. Cosofret, M. Erdosy, T.A. Johnson, R.P. Buck, R.B. Ash, M.R. Neuman, Microfabricated sensor arrays sensitive to pH and K+ for ionic distribution measurements in the beating heart. Anal. Chem. 67(10), 1647–1653 (1995)CrossRefGoogle Scholar
  278. 278.
    S.A.M. Marzouk, S. Ufer, R.P. Buck, T.A. Johnson, L.A. Dunlap, W.E. Cascio, Electrodeposited iridium oxide pH electrode for measurement of extracellular myocardial acidosis during acute ischemia. Anal. Chem. 70(23), 5054–5061 (1998)CrossRefGoogle Scholar
  279. 279.
    J.L. Gonzalez-Guillaumin, D.C. Sadowski, K.V.I.S. Kaler, M.P. Mintchev, Ingestible capsule for impedance and pH monitoring in the esophagus. IEEE Trans. Biomed. Eng. 54(12), 2231–2236 (2007)CrossRefGoogle Scholar
  280. 280.
    I.B. Tahirbegi, M. Mir, J. Samitier, Real-time monitoring of ischemia inside stomach. Biosens. Bioelectron. 40(1), 323–328 (2013)CrossRefGoogle Scholar
  281. 281.
    I.B. Tahirbegi, M. Mir, S. Schostek, M. Schurr, J. Samitier, In vivo ischemia monitoring array for endoscopic surgery. Biosens. Bioelectron. 61, 124–130 (2014)CrossRefGoogle Scholar
  282. 282.
    M. Mir, R. Lugo, I.B. Tahirbegi, J. Samitier, Miniaturizable ion-selective arrays based on highly stable polymer membranes for biomedical applications. Sensors 14(7), 11844–11854 (2014)CrossRefGoogle Scholar
  283. 283.
    M. Kubon et al., A microsensor system to probe physiological environments and tissue response, in 2010 IEEE Sensors, (2010), pp. 2607–2611Google Scholar
  284. 284.
    A. Weltin, B. Enderle, J. Kieninger, G.A. Urban, Multiparametric, flexible microsensor platform for metabolic monitoring. IEEE Sens. J. 14(10), 3345–3351 (2014)CrossRefGoogle Scholar
  285. 285.
    G. Urban et al., Miniaturized multi-enzyme biosensors integrated with pH sensors on flexible polymer carriers for in vivo applications. Biosens. Bioelectron. 7(10), 733–739 (1992)CrossRefGoogle Scholar
  286. 286.
    A. Guiseppi-Elie, S. Brahim, G. Slaughter, K.R. Ward, Design of a subcutaneous implantable biochip for monitoring of glucose and lactate. IEEE Sens. J. 5(3), 345–355 (2005)CrossRefGoogle Scholar
  287. 287.
    A.R.A. Rahman, G. Justin, A. Guiseppi-Elie, Towards an implantable biochip for glucose and lactate monitoring using microdisc electrode arrays (MDEAs). Biomed. Microdevices 11(1), 75–85 (2008)CrossRefGoogle Scholar
  288. 288.
    A.R.A. Rahman, G. Justin, A. Guiseppi-Wilson, A. Guiseppi-Elie, Fabrication and packaging of a dual sensing electrochemical biotransducer for glucose and lactate useful in intramuscular physiologic status monitoring. IEEE Sens. J. 9(12), 1856–1863 (2009)CrossRefGoogle Scholar
  289. 289.
    C.N. Kotanen, A. Guiseppi-Elie, Characterization of a wireless potentiostat for integration with a novel implantable biotransducer. IEEE Sens. J. 14(3), 768–776 (2014)CrossRefGoogle Scholar
  290. 290.
    M. Stanacevic, K. Murari, A. Rege, G. Cauwenberghs, N.V. Thakor, VLSI potentiostat array with oversampling gain modulation for wide-range neurotransmitter sensing. IEEE Trans. Biomed. Circuits Syst. 1(1), 63–72 (2007)CrossRefGoogle Scholar
  291. 291.
    M. Mollazadeh, K. Murari, G. Cauwenberghs, N. Thakor, Wireless micropower instrumentation for multimodal acquisition of electrical and chemical neural activity. IEEE Trans. Biomed. Circuits Syst. 3(6), 388–397 (2009)CrossRefGoogle Scholar
  292. 292.
    M. Roham et al., A wireless IC for wide-range neurochemical monitoring using amperometry and fast-scan cyclic voltammetry. IEEE Trans. Biomed. Circuits Syst. 2(1), 3–9 (2008)CrossRefGoogle Scholar
  293. 293.
    G. Massicotte, S. Carrara, G. Di Micheli, M. Sawan, A CMOS amperometric system for multi-neurotransmitter detection. IEEE Trans. Biomed. Circuits Syst., 10(3), 731–741 (2016)Google Scholar
  294. 294.
    P. Valdastri et al., An implantable ZigBee ready telemetric platform for in vivo monitoring of physiological parameters. Sens. Actuators Phys. 142(1), 369–378 (2008)CrossRefGoogle Scholar
  295. 295.
    H. Liu et al., An implantable radio-telemetry system for detecting multiple bio-parameters of a small animal based on wireless energy transmission. Mechatronics 28, 18–26 (2015)CrossRefGoogle Scholar
  296. 296.
    S. Carrara et al., Remote system for monitoring animal models with single-metabolite bio-nano-sensors. IEEE Sens. J. 13(3), 1018–1024 (2013)MathSciNetCrossRefGoogle Scholar
  297. 297.
    A. Cavallini et al., A subcutaneous biochip for remote monitoring of human metabolism: packaging and biocompatibility assessment. IEEE Sens. J. 15(1), 417–424 (2015)CrossRefGoogle Scholar
  298. 298.
    C. Baj-Rossi et al., Full fabrication and packaging of an implantable multi-panel device for monitoring of metabolites in small animals. IEEE Trans. Biomed. Circuits Syst. 8(5), 636–647 (2014)CrossRefGoogle Scholar
  299. 299.
    F. Xu, G. Yan, K. Zhao, L. Lu, J. Gao, G. Liu, A wireless capsule system with ASIC for monitoring the physiological signals of the human gastrointestinal tract. IEEE Trans. Biomed. Circuits Syst. 8(6), 871–880 (2014)CrossRefGoogle Scholar
  300. 300.
    L. Lu, G. Yan, K. Zhao, F. Xu, An implantable telemetry platform system with ASIC for in vivo monitoring of gastrointestinal physiological information. IEEE Sens. J. 15(6), 3524–3534 (2015)CrossRefGoogle Scholar
  301. 301.
    W.P. Chan et al., A monolithically integrated pressure/oxygen/temperature sensing SoC for multimodality intracranial neuromonitoring. IEEE J. Solid-State Circuits 49(11), 2449–2461 (2014)CrossRefGoogle Scholar
  302. 302.
    C.N. Kotanen, A. Guiseppi-Elie, Monitoring systems and quantitative measurement of biomolecules for the management of trauma. Biomed. Microdevices 15(3), 561–577 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.The Hamlyn CentreImperial College LondonLondonUK

Personalised recommendations