Potential of a smartphone as a stress-free sensor of daily human behaviour

Koki Mimura; Hirohisa Kishino; Genta Karino; Etsuko Nitta; Aya Senoo; Kentaro Ikegami; Tetsuya Kunikata; Hideo Yamanouchi; Shun Nakamura; Kan Sato; Mamiko Koshiba

doi:10.1016/j.bbr.2014.06.007

Potential of a smartphone as a stress-free sensor of daily human behaviour

Behav Brain Res. 2015 Jan 1:276:181-9. doi: 10.1016/j.bbr.2014.06.007. Epub 2014 Jun 13.

Authors

Affiliations

¹ Tokyo University of Agriculture and Technology, Tokyo, Japan.
² The University of Tokyo, Tokyo, Japan.
³ Tokyo University of Agriculture and Technology, Tokyo, Japan; The National Center of Neurology and Psychiatry, Tokyo, Japan.
⁴ Tokyo University of Agriculture and Technology, Tokyo, Japan; Saitama Medical University, Saitama, Japan.
⁵ Saitama Medical University, Saitama, Japan.
⁶ Tokyo University of Agriculture and Technology, Tokyo, Japan; Saitama Medical University, Saitama, Japan; The National Center of Neurology and Psychiatry, Tokyo, Japan. Electronic address: koshiba@saitama-med.ac.jp.

PMID: 24933187
DOI: 10.1016/j.bbr.2014.06.007

Abstract

Behaviour is one of the most powerful objective signals that connotes psychological functions regulated by neuronal network systems. This study searched for simple behaviours using smartphone sensors with three axes for measuring acceleration, angular speed and direction. We used quantitative analytic methodology of pattern recognition for work contexts, individual workers and seasonal effects in our own longitudinally recorded data. Our 13 laboratory members were involved in the care of common marmosets and domestic chicks, which lived in separate rooms. They attached a smartphone to their front waist-belts during feeding and cleaning in five care tasks. Behavioural characteristics such as speed, acceleration and azimuth, pitch, and roll angles were monitored. Afterwards, participants noted subjective scores of warmth sensation and work efficiency. The multivariate time series behavioral data were characterized by the subjective scores and environmental factors such as room temperature, season, and humidity, using the linear mixed model. In contrast to high-precision but stress-inducing sensors, the mobile sensors measuring daily behaviours allowed us to quantify the effects of the psychological states and environmental factors on the behavioural traits.

Keywords: Accelerometer; Geomagnetic sensor; Gyroscope; Seasonal modulation; Thermal psychology; Work efficiency.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Cell Phone*
Environment*
Female
Humans
Humidity
Locomotion*
Male
Middle Aged
Remote Sensing Technology / instrumentation*
Seasons
Temperature
Work / psychology*
Young Adult