Readiness of smartphones for data collection and data mining with an example application in mental health

Darren Yates, Md Zahidul Islam

Research output: Book chapter/Published conference paperConference paper


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.

Original languageEnglish
Title of host publicationData Mining - 17th Australasian Conference, AusDM 2019, Proceedings
EditorsThuc D. Le, Lin Liu, Kok-Leong Ong, Yanchang Zhao, Warren H. Jin, Sebastien Wong, Graham Williams
Number of pages12
ISBN (Print)9789811516986
Publication statusPublished - 23 Nov 2019
Event17th Australasian Conference on Data Mining: AusDM 2019 - InterContinental Adelaide at North Terrace, Adelaide, Australia
Duration: 02 Dec 201905 Dec 2019 (program)

Publication series

NameCommunications in Computer and Information Science
Volume1127 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference17th Australasian Conference on Data Mining
Internet address

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