Smartphone Sensor Data for Identifying and Monitoring Symptoms of Mood Disorders: A longitudinal observational study (Preprint)

BACKGROUND Mood disorders are burdensome illnesses that often go undetected and untreated. Sensor technologies within smartphones may provide an opportunity for identifying the early changes in circadian rhythm and social support/connectedness that signify the onset of a depressive or manic episode. OBJECTIVE Using smartphone sensor data, this study investigated the relationship between circadian rhythm, determined by Global Positioning Systems (GPS) data, and symptoms of mental health among a clinical sample of adults diagnosed with Major Depressive Disorder (MDD) or Bipolar Disorder (BD). METHODS A total of 121 participants were recruited from a clinical setting to take part in a ten-week observational study. Self-report questionnaires for mental health outcomes, social support, social connectedness, and quality of life were assessed at six timepoints throughout the study period. Participants consented to passively sharing their smartphone GPS data for the duration of the study. Circadian rhythm (i.e., regularity of location changes in a 24-hour rhythm) was extracted from GPS mobility patterns at baseline. RESULTS While we found no association between circadian rhythm and mental health functioning at baseline, there was a positive association between circadian rhythm and the size of participants social support network at baseline (r = .22, p = .030, R2 = .049). In participants with BD, circadian rhythm was associated with change in anxiety from baseline, whereby higher circadian rhythm was associated with an increase in anxiety and lower circadian rhythm was associated with a decrease in anxiety at timepoint five. CONCLUSIONS Circadian rhythm, extracted from smartphone GPS data, was associated with social support and predicted changes in anxiety in a clinical sample of adults with mood disorders. Larger studies are required for further validations. However, smartphone sensing may have the potential to monitor early symptoms of mood disorders.

Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer

The streaming and recording of smartphone sensor signals is desirable for mHealth, telemedicine, environmental monitoring and other applications. Time series data gathered in these fields typically benefit from the time-synchronized integration of different sensor signals. However, solutions required for this synchronization are mostly available for stationary setups. We hope to contribute to the important emerging field of portable data acquisition by presenting open-source Android applications both for the synchronized streaming (Send-a) and recording (Record-a) of multiple sensor data streams. We validate the applications in terms of functionality, flexibility and precision in fully mobile setups and in hybrid setups combining mobile and desktop hardware. Our results show that the fully mobile solution is equivalent to well-established desktop versions. With the streaming application Send-a and the recording application Record-a, purely smartphone-based setups for mobile research and personal health settings can be realized on off-the-shelf Android devices.

The application of smartphone sensors to promote cognitive abilities easier and more effective physics learning

The use of sensor on smartphones as physics learning media encourages teachers to reconstruct teaching methods. This paper presents the effect on students’ cognitive abilities using an accelerometer and a gyroscope sensor simultaneously in learning circular motion, as well as students’ responses and the effectiveness of sensor media on smartphones used. A pre-experimental research design was used in this study which involved 12 students of XII MIPA at SMA Negeri 1 Pagaden Subang Jawa Barat. They learned circular motion guided by the smartphone sensors-based worksheets and were tested using an essay test for cognitive abilities measurements. Meanwhile, students’ responses and the effectiveness were obtained using a Likert scale questionnaire. The improvement of students’ cognitive abilities was significantly higher than the pretest which was obtained from the N-gain with a final value of 0.41. Worksheets using smartphone sensor media were more effective than conventional learning. In addition, students showed a positive response in which 93.75% of students were interested, 85,42% were motivated to learn the circular motion, and 91.14% of students became easier in understanding physics concepts.

Rancang Bangun Sistem Pemantau Keamanan Rumah Dari Tindak Pencurian Berbasis Android Secara Waktu Nyata

Dalam keadaan ekonomi yang sulit di masa pandemi COVID-19 ini, tindak kejahatan menjadi meningkat. Salah satunya yaitu tindak pencurian pada rumah yang ditinggal bekerja oleh penghuninya. Cara yang biasa digunakan untuk mengatasi permasalahan ini yaitu dengan mempekerjakan petugas keamanan atau memasang kamera CCTV. Pada penelitian ini diajukan sebuah sistem pemantauan rumah yang dapat mendeteksi seorang penyusup yang bergerak di depan dan di samping rumah, serta penyusup yang hendak membuka pintu depan dan pintu samping rumah. Sistem dapat memberitahu penghuni rumah dan petugas keamanan jika mendeteksi adanya penyusup melalui aplikasi Android pada smartphone. Sensor Passive Infrared (PIR) dipasang pada area dekat pintu depan dan samping rumah untuk mendeteksi pergerakan orang. Pada pintu depan dan samping dipasang sensor magnetic door switch untuk mendeteksi pembobolan pintu. Data-data sensor diproses oleh WeMos D1 Mini yang terkoneksi WiFi. Ketika status waspada dan bahaya terdeteksi, buzzer di depan rumah akan menyala dan WeMos langsung mengirimkan notifikasi berupa status kondisi rumah ke Android pemilik rumah dan petugas keamanan kompleks perumahan setempat. Berdasarkan hasil pengujian, sistem ini dapat mendeteksi pergerakan manusia di area depan dan samping rumah dengan jarak maksimum 5 meter dari sensor. Berdasarkan hasil pendeteksian magnetic door switch, sistem dapat mengirimkan notifikasi berupa status waspada dan bahaya ke Android pemilik rumah dan petugas keamanan kompleks perumahan setempat dengan waktu pengiriman dari 1 sampai 5 detik. Notifikasi tersebut dapat diterima Android dalam keadaan lock screen maupun dalam keadaan sedang membuka aplikasi lain.