Abstract
Smartphones have become the ultimate ‘personal’ computers with sufficient processing power and storage to perform machine learning tasks. Building on our previous research, this paper investigates an example practical application of this capability, combining it with a smartphone’s on-board sensors to develop a personalised, self-contained machine-learning framework for monitoring mental health. We present a mobile application for Android devices called ‘Mindful’ that incorporates data collection from the phone’s sensors and data sources, pre-processes the data locally and executes data mining on that data to provide pre-emptive feedback to the phone user about their mind state. Rather than as a finished product, this application is presented as a first step to show that from a technological perspective, smartphones are well equipped to perform this type of role. We invite colleagues from the mental health sciences to join us in furthering this work into a smart monitor for mental health.
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Yates, D., Islam, M.Z. (2019). Readiness of Smartphones for Data Collection and Data Mining with an Example Application in Mental Health. In: Le, T., et al. Data Mining. AusDM 2019. Communications in Computer and Information Science, vol 1127. Springer, Singapore. https://doi.org/10.1007/978-981-15-1699-3_19
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DOI: https://doi.org/10.1007/978-981-15-1699-3_19
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