Abstract
Smartphones and portable media devices are both equipped with sensor components, such as accelerometers. A software application enables these devices to function as a robust wireless accelerometer platform. The recorded accelerometer waveform can be transmitted wireless as an e-mail attachment through connectivity to the Internet. The implication of such devices as a wireless accelerometer platform is the experimental and post-processing locations can be placed anywhere in the world. Gait was quantified by mounting a smartphone or portable media device proximal to the lateral malleolus of the ankle joint. Attributes of the gait cycle were quantified with a considerable accuracy and reliability. The patellar tendon reflex response was quantified by using the device in tandem with a potential energy impact pendulum to evoke the patellar tendon reflex. The acceleration waveform maximum acceleration feature of the reflex response displayed considerable accuracy and reliability. By mounting the smartphone or portable media device to the dorsum of the hand through a glove, Parkinson’s disease hand tremor was quantified and contrasted with significance to a non-Parkinson’s disease steady hand control. With the methods advocated in this chapter, any aspect of human movement may be quantified through smartphones or portable media devices and post-processed anywhere in the world. These wearable devices are anticipated to substantially impact the biomedical and healthcare industry.
Key words
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
LeMoyne R, Mastroianni T, Cozza M, Coroian C, Grundfest W (2010) Implementation of an iPhone for characterizing Parkinson’s disease tremor through a wireless accelerometer application. In Proceedings of the 32nd Annual International Conference of the IEEE EMBS, pp 4954–4958
LeMoyne R, Mastroianni T, Cozza M, Coroian C, Grundfest W (2010) Implementation of an iPhone as a wireless accelerometer for quantifying gait characteristics. In Proceedings of the 32nd Annual International Conference of the IEEE EMBS, pp 3847–3851
LeMoyne R, Mastroianni T, Grundfest W (2011) Wireless accelerometer iPod application for quantifying gait characteristics. In Proceedings of the 33rd Annual International Conference of the IEEE EMBS, pp 7904–7907
LeMoyne R, Mastroianni T, Grundfest W, (2012) Quantified reflex strategy using an iPod as a wireless accelerometer application. In Proceedings of 34th International Conference of the IEEE EMBS, pp 2476–2479
LeMoyne R, Mastroianni T, Grundfest W, Nishikawa K (2013) Implementation of an iPhone wireless accelerometer application for the quantification of reflex response. In Proceedings of 35th International Conference of the IEEE EMBS, pp 4658–4661
Patel S, Park H, Bonato P, Chan L, Rodgers M (2012) A review of wearable sensors and systems with application in rehabilitation. J Neuroeng Rehabil 9:21
LeMoyne R, Coroian C, Mastroianni T, Opalinski P, Cozza M, Grundfest W (2009) The merits of artificial proprioception, with applications in biofeedback gait rehabilitation concepts and movement disorder characterization. In: Barros de Mello CA (ed) Biomedical engineering. Vienna, Austria, Intech, Ch 10
Culhane KM, O’Connor M, Lyons D, Lyons GM (2005) Accelerometers in rehabilitation medicine for older adults. Age Ageing 34:556–560
Jovanov E, Milenkovic A, Otto C, de Groen PC (2005) A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. J Neuroeng Rehabil 2:6
Saremi K, Marehbian J, Yan X, Regnaux JP, Elashoff R, Bussel B, Dobkin BH (2006) Reliability and validity of bilateral thigh and foot accelerometry measures of walking in healthy and hemiparetic subjects. Neurorehabil Neural Repair 20:297–305
Kavanagh JJ, Morrison S, James DA, Barrett R (2006) Reliability of segmental accelerations measured using a new wireless gait analysis system. J Biomech 39:2863–2872
Kavanagh J, Barrett R, Morrison S (2006) The role of the neck and trunk in facilitating head stability during walking. Exp Brain Res 172:454–463
LeMoyne R, Mastroianni T, Coroian C, Grundfest W (2011) Tendon reflex and strategies for quantification, with novel methods incorporating wireless accelerometer reflex quantification devices, a perspective review. J Mech Med Biol 11:471–513
Lee JA, Cho SH, Lee JW, Lee KH, Yang HK (2007) Wearable accelerometer system for measuring the temporal parameters of gait. In Proceedings of the 29th Annual International Conference of the IEEE EMBS, pp 483–486
Lee JA, Cho SH, Lee YJ, Yang HK, Lee JW (2010) Portable activity monitoring system for temporal parameters of gait cycles. J Med Syst 34:959–966
Bamberg SJ, Benbasat AY, Scarborough DM, Krebs DE, Paradiso JA (2008) Gait analysis using a shoe-integrated wireless sensor system. IEEE Trans Inf Technol Biomed 12:413–423
LeMoyne R, Coroian C, Mastroianni T, Grundfest W (2009) Wireless accelerometer assessment of gait for quantified disparity of hemiparetic locomotion. J Mech Med Biol 9:329–343
LeMoyne R, Coroian C, Mastroianni T (2009) Wireless accelerometer system for quantifying gait. In Proceedings of the IEEE/ICME International Conference on Complex Medical Engineering (CME), pp 1–4
LeMoyne R, Coroian C, Mastroianni T, Grundfest W (2008) Virtual proprioception. J Mech Med Biol 8:317–338
LeMoyne R, Coroian C, Mastroianni T, Wu W, Grundfest W, Kaiser W (2008) Virtual proprioception with real-time step detection and processing. In Proceedings of the 30th Annual International Conference of the IEEE EMBS, pp 4238–4241
Mizuike C, Ohgi S, Morita S (2009) Analysis of stroke patient walking dynamics using a tri-axial accelerometer. Gait Posture 30:60–64
Guo Y, Wu D, Liu G, Zhao G, Huang B, Wang L (2012) A low-cost body inertial-sensing network for practical gait discrimination of hemiplegia patients. Telemed J E Health 18:748–754
Prajapati SK, Gage WH, Brooks D, Black SE, McIlroy WE (2011) A novel approach to ambulatory monitoring: investigation into the quantity and control of everyday walking in patients with subacute stroke. Neurorehabil Neural Repair 25:6–14
Bugané F, Benedetti MG, Casadio G, Attala S, Biagi F, Manca M, Leardini A (2012) Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: validation on normal subjects by standard gait analysis. Comput Methods Programs Biomed 108:129–137
Watanabe T, Saito H, Koike E, Nitta K (2011) A preliminary test of measurement of joint angles and stride length with wireless inertial sensors for wearable gait evaluation system. Comput Intell Neurosci 2011: 975193
Djurić-Jovičić MD, Jovičić NS, Popović DB (2011) Kinematics of gait: new method for angle estimation based on accelerometers. Sensors 11:10571–10585
Kavanagh JJ (2009) Lower trunk motion and speed-dependence during walking. J Neuroeng Rehabil 6:9
Lai DT, Charry E, Begg R, Palaniswami M (2008) A prototype wireless inertial-sensing device for measuring toe clearance. In Proceedings of the 30th Annual International Conference of the IEEE EMBS, pp 4899–4902
Reininga IH, Stevens M, Wagenmakers R, Bulstra SK, Groothoff JW, Zijlstra W (2012) Subjects with hip osteoarthritis show distinctive patterns of trunk movements during gait-a body-fixed-sensor based analysis. J Neuroeng Rehabil 9:3
Tura A, Raggi M, Rocchi L, Cutti AG, Chiari L (2010) Gait symmetry and regularity in transfemoral amputees assessed by trunk accelerations. J Neuroeng Rehabil 7:4
Tura A, Rocchi L, Raggi M, Cutti AG, Chiari L (2012) Recommended number of strides for automatic assessment of gait symmetry and regularity in above-knee amputees by means of accelerometry and autocorrelation analysis. J Neuroeng Rehabil 9:11
Hsu CC, Chen JH (2011) A novel sensor-assisted RFID-based indoor tracking system for the elderly living alone. Sensors 11:10094–10113
Yeoh WS, Pek I, Yong YH, Chen X, Waluyo AB (2008) Ambulatory monitoring of human posture and walking speed using wearable accelerometer sensors. In Proceedings of the 30th Annual International Conference of the IEEE EMBS, pp 5184–5187
Choquette S, Hamel M, Boissy P (2008) Accelerometer-based wireless body area network to estimate intensity of therapy in post-acute rehabilitation. J Neuroeng Rehabil 5:20
Hurkmans HL, Ribbers GM, Streur-Kranenburg MF, Stam HJ, van den Berg-Emons RJ (2011) Energy expenditure in chronic stroke patients playing Wii Sports: a pilot study. J Neuroeng Rehabil 8:38
Huang H, Wolf SL, He J (2006) Recent developments in biofeedback for neuromotor rehabilitation. J Neuroeng Rehabil 3:11
McGregor SJ, Armstrong WJ, Yaggie JA, Bollt EM, Parshad R, Bailey JJ, Johnson SM, Goin AM, Kelly SR (2011) Lower extremity fatigue increases complexity of postural control during a single-legged stance. J Neuroeng Rehabil 8:43
Dozza M, Chiari L, Chan B, Rocchi L, Horak FB, Cappello A (2005) Influence of a portable audio-biofeedback device on structural properties of postural sway. J Neuroeng Rehabil 2:13
Lee BC, Kim J, Chen S, Sienko KH (2012) Cell phone based balance trainer. J Neuroeng Rehabil 9:10
Djurić-Jovičić MD, Jovičić NS, Popović DB, Djordjević AR (2012) Nonlinear optimization for drift removal in estimation of gait kinematics based on accelerometers. J Biomech 45:2849–2854
Weenk D, van Beijnum BJ, Baten CT, Hermens HJ, Veltink PH (2013) Automatic identification of inertial sensor placement on human body segments during walking. J Neuroeng Rehabil 10:31
LeMoyne R, Mastroianni T, Cozza M, Coroian C (2010) Quantification of gait characteristics through a functional iPhone wireless accelerometer application mounted to the spine. In Proceedings of ASME 2010 5th Frontiers in Biomedical Devices Conference (BioMed), pp 87–88
LeMoyne R, Mastroianni T, Cozza M, Coroian C (2010) iPhone wireless accelerometer application for acquiring quantified gait attributes. In Proceedings of ASME 2010 5th Frontiers in Biomedical Devices Conference (BioMed), pp 19–20
LeMoyne R, Mastroianni T (2012) iWalk, a gait analysis device incorporating an iPod wireless accelerometer application. In Proceedings of 42nd Society for Neuroscience Annual Meeting, New Orleans, LA, October 13–17, 2012
Nishiguchi S, Yamada M, Nagai K, Mori S, Kajiwara Y, Sonoda T, Yoshimura K, Yoshitomi H, Ito H, Okamoto K, Ito T, Muto S, Ishihara T, Aoyama T (2012) Reliability and validity of gait analysis by android-based smartphone. Telemed J E Health 18:292–296
Yamada M, Aoyama T, Mori S, Nishiguchi S, Okamoto K, Ito T, Muto S, Ishihara T, Yoshitomi H, Ito H (2012) Objective assessment of abnormal gait in patients with rheumatoid arthritis using a smartphone. Rheumatol Int 32:3869–3874
Mellone S, Tacconi C, Chiari L (2012) Validity of a smartphone-based instrumented timed up and go. Gait Posture 36:163–165
Palmerini L, Mellone S, Rocchi L, Chiari L (2011) Dimensionality reduction for the quantitative evaluation of a smartphone-based timed up and go test. In Proceedings of the 33rd Annual International Conference of the IEEE EMBS, pp 7179–7182
Wagner R, Ganz A (2012) PAGAS: portable and accurate gait analysis system. In Proceedings of the 34th Annual International Conference of the IEEE EMBS, pp 280–283
LeMoyne R (2010) Wireless quantified reflex device, Ph.D. dissertation, UCLA, Biomed. Eng. IDP
LeMoyne R, Coroian C, Mastroianni T, Grundfest W (2008) Quantified deep tendon reflex device for response and latency, third generation. J Mech Med Biol 8:491–506
LeMoyne R, Mastroianni T, Kale H, Luna J, Stewart J, Elliot S, Bryan F, Coroian C, Grundfest W (2011) Fourth generation wireless reflex quantification system for acquiring tendon reflex response and latency. J Mech Med Biol 11:31–54
LeMoyne R, Coroian C, Mastroianni T, (2009) Wireless accelerometer reflex quantification system characterizing response and latency. In Proceedings of 31st Annual International Conference of the IEEE EMBS, pp 5283–5286
LeMoyne R, Jafari R (2006) Quantified deep tendon reflex device, second generation. In Proceedings of 15th International Conference on Mechanics in Medicine and Biology ICMMB-15 2006, 6–8 December 2006, Furama Riverfront, Singapore
LeMoyne R, Dabiri F, Jafari R (2008) Quantified deep tendon reflex device, second generation. J Mech Med Biol 8:75–85
LeMoyne R, Jafari R, Jea D (2005) Fully quantified evaluation of myotatic stretch reflex. In Proceedings of 35th Society for Neuroscience Annual Meeting, Washington, DC, November 12–16, 2005
LeMoyne R., Dabiri F., Coroian C., Mastroianni T., Grundfest W. (2007) Quantified deep tendon reflex device for assessing response and latency. In Proceedings of 37th Society for Neuroscience Annual Meeting, San Diego, CA, November 3–7, 2007
LeMoyne R., Coroian C., Mastroianni T., Cozza M., Grundfest W. (2010) Quantification of reflex response through an iPhone wireless accelerometer application. In Proceedings of 40th Society for Neuroscience Annual Meeting, San Diego, CA, November 13–17, 2010
LeMoyne R., Mastroianni T. (2011) Reflex response quantification using an iPod wireless accelerometer application. In Proceedings of 41st Society for Neuroscience Annual Meeting, Washington, DC, November 12–16, 2011
Seeley RR, Stephens TD, Tate P (2003) Anatomy and physiology. McGraw-Hill, New York, NY
Kandel ER, Schwartz JH, Jessell TM (2000) Principles of neural science. McGraw-Hill, New York, NY
Diamond MC, Scheibel AB, Elson LM (1985) The human brain coloring book. Harper Perennial, New York, NY
Bickley LS, Szilagyi PG (2003) Bates’ guide to physical examination and history taking. Lippincott Williams and Wilkins, New York, NY
Nolte J, Sundsten JW (2002) The human brain: an introduction to its functional anatomy. Mosby, St. Louis, MO
Volkmann J, Moro E, Pahwa R (2006) Basic algorithms for the programming of deep brain stimulation in Parkinson’s disease. Mov Disord 21:S284–S289
Rouse AG, Stanslaski SR, Cong P, Jensen RM, Afshar P, Ullestad D, Gupta R, Molnar GF, Moran DW, Denison TJ (2011) A chronic generalized bi-directional brain-machine interface. J Neural Eng 8:1–36
Obwegeser AA, Uitti RJ, Witte RJ, Lucas JA, Turk MF, Wharen RE Jr (2001) Quantitative and qualitative outcome measures after thalamic deep brain stimulation to treat disabling tremors. Neurosurgery 48:274–281
Kumru H, Summerfield C, Valldeoriola F, Valls-Solé J (2004) Effects of subthalamic nucleus stimulation on characteristics of EMG activity underlying reaction time in Parkinson’s disease. Mov Disord 19:94–100
Keijsers NL, Horstink MW, Gielen SC (2006) Ambulatory motor assessment in Parkinson’s disease. Mov Disord 21:34–44
Keijsers NL, Horstink MW, van Hilten JJ, Hoff JI, Gielen CC (2000) Detection and assessment of the severity of levodopa-induced dyskinesia in patients with Parkinson’s disease by neural networks. Mov Disord 15:1104–1111
Gurevich TY, Shabtai H, Korczyn AD, Simon ES, Giladi N (2006) Effect of rivastigmine on tremor in patients with Parkinson’s disease and dementia. Mov Disord 21:1663–1666
Schrag A, Schelosky L, Scholz U, Poewe W (1999) Reduction of Parkinsonian signs in patients with Parkinson’s disease by dopaminergic versus anticholinergic single-dose challenges. Mov Disord 14:252–255
Weiss A, Sharifi S, Plotnik M, van Vugt JP, Giladi N, Hausdorff JM (2011) Toward automated, at-home assessment of mobility among patients with Parkinson disease, using a body-worn accelerometer. Neurorehabil Neural Repair 25:810–818
LeMoyne R, Coroian C, Mastroianni T (2009) Quantification of Parkinson’s disease characteristics using wireless accelerometers. In Proceedings of the IEEE/ICME International Conference on Complex Medical Engineering (CME), pp 1–5
Giuffrida JP, Riley DE, Maddux BN, Heldman DA (2009) Clinically deployable Kinesia technology for automated tremor assessment. Mov Disord 24:723–730
Cancela J, Pansera M, Arredondo MT, Estrada JJ, Pastorino M, Pastor-Sanz L, Villalar JL (2010) A comprehensive motor symptom monitoring and management system: the bradykinesia case. In Proceedings of the 32nd Annual International Conference of the IEEE EMBS, pp 1008–1011
Pastorino M, Cancela J, Arredondo MT, Pansera M, Pastor-Sanz L, Villagra F, Pastor MA, Martin JA (2011) Assessment of bradykinesia in Parkinson’s disease patients through a multi-parametric system. In Proceedings of the 33rd Annual International Conference of the IEEE EMBS, pp 1810–1813
Cancela J, Pastorino M, Arredondo MT, Pansera M, Pastor-Sanz L, Villagra F, Pastor MA, Gonzalez AP (2011) Gait assessment in Parkinson’s disease patients through a network of wearable accelerometers in unsupervised environments. In Proceedings of the 33rd Annual International Conference of the IEEE EMBS, pp 2233–2236
Kostikis N, Hristu-Varsakelis D, Arnaoutoglou M, Kotsavasiloglou C, Baloyiannis S (2011) Towards remote evaluation of movement disorders via smartphones. In Proceedings of the 33rd Annual International Conference of the IEEE EMBS, pp 5240–5243
LeMoyne R, Mastroianni T, Grundfest W (2013) Wireless accelerometer configuration for monitoring Parkinson’s disease hand tremor. Adv Parkinson Dis 2:62–67
Acknowledgement
The author would like to thank IEEE for granting permission to reuse the content (Figs. 1, 2, 3, 4, 5, 6, 7, 8, and 9 and Tables 1 and 2) of refs. 1, 2, and 4. I would personally like to acknowledge the contributions of Dr. Grundfest of UCLA Department of Bioengineering, as his insight and expertise served an instrumental role for the advance of smartphones and portable media devices as a wireless accelerometer platform for the quantification of gait, tendon reflex response, and Parkinson’s disease hand tremor. I would like to extend my appreciation to Kevin Zanjani, Michael Minicozzi, and Anthony Hessel for their assistance with the final preparation of the manuscript.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Science+Business Media New York
About this protocol
Cite this protocol
LeMoyne, R., Mastroianni, T. (2015). Use of Smartphones and Portable Media Devices for Quantifying Human Movement Characteristics of Gait, Tendon Reflex Response, and Parkinson’s Disease Hand Tremor. In: Rasooly, A., Herold, K. (eds) Mobile Health Technologies. Methods in Molecular Biology, vol 1256. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2172-0_23
Download citation
DOI: https://doi.org/10.1007/978-1-4939-2172-0_23
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-2171-3
Online ISBN: 978-1-4939-2172-0
eBook Packages: Springer Protocols