Scale-free dynamics of human behavior in personal computer operations

Egi, Masashi; Ishikawa, Hiroshi

doi:10.1145/3281375.3281381

Cited by 3 publications

(4 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The devices were selected for the validation of the concept according to the previous studies as follows. For the behaviour layer, a home‐made wrist‐band type activity tracker (Life logger) and the PC logger recording event‐logs of keyboard and mouse operations were used for monitoring the lifestyle [ 12 ] and the workstyle [ 13 ], respectively. The wrist‐band type activity tracker had a triaxial accelerometer to provide the number of steps, the index of exercise intensity in metabolic equivalents, etc.…”

Section: Devices Trial In Office and Analysismentioning

confidence: 99%

“…The wrist‐band type activity tracker had a triaxial accelerometer to provide the number of steps, the index of exercise intensity in metabolic equivalents, etc. By using the key/mouse data recorded over the daily course, a fractal dimension was obtained as a slope of fitted line for cumulative distribution vs time‐interval of key/mouse events graph [ 13 ]. The fractal dimension represents a kind of rhythm of PC operations, which depends on the mood state.…”

Section: Devices Trial In Office and Analysismentioning

confidence: 99%

See 1 more Smart Citation

Proposal of layered mental healthcare for mental well‐being

Kiguchi

Sutoko

Atsumori

et al. 2021

Healthcare Tech Letters

Self Cite

View full text Add to dashboard Cite

A new concept, 'Layered mental healthcare' for keeping employees mental well-being in the workplace to avoid losses caused by both absenteeism and presenteeism is proposed.A key factor forming the basis of the concept is the biometric measurements over three layers, i.e., behaviour, physiology, and brain layers, for monitoring mental/distress conditions of employees. Here, the necessity of measurements in three layers was validated by the data-driven approach using the preliminary dataset measured in the office environment. Biometric measurements were supported by an activity tracker, a PC logger, and the optical topography; mental/distress conditions were quantified by the brief job stress questionnaire. The biometric features obtained 1 week before the measurement of mental/distress scores were selected for the best regression model. The feature importance of each layer was obtained in the learning process of the best model using the light graded boosting machine and was compared between layers. The ratio of feature importance of behaviour:physiology:brain layers was found to be 4:3:3. The study results suggest the contribution and necessity of the three-layer features in predicting mental/distress scores.

show abstract

Section: Devices Trial In Office and Analysismentioning

confidence: 99%

Section: Devices Trial In Office and Analysismentioning

confidence: 99%

Proposal of layered mental healthcare for mental well‐being

Kiguchi

Sutoko

Atsumori

et al. 2021

Healthcare Tech Letters

Self Cite

View full text Add to dashboard Cite

show abstract

“…Using the key/mouse data recorded over the course of a day, a fractal dimension was obtained as a slope of fitted line for cumulative distribution vs. timeinterval graph. Because the fractal dimension also depends on the workload in a day, the key/mouse index d key/mouse for the day was obtained as a deviation from the fractal dimension stemming from workload (5).…”

Section: Multimodality Measurementsmentioning

confidence: 99%

“…These have been independently used in several studies on mental healthcare application. The fractal dimensions obtained from the PC logger data are expected to be related with mood states (5). The usage of the wrist-band type activity tracker for judgments of reinstatement reduced the ratio of re-leave (6).…”

Section: Introductionmentioning

confidence: 99%

Mental Condition Monitoring Based on Multimodality Biometry

Kiguchi

Sutoko

Atsumori

et al. 2020

Front. Public Health

Self Cite

View full text Add to dashboard Cite

We have developed a system with multimodality that monitors objective biomarkers for screening the mental distress in the office. A field study using a prototype of the system was performed over four months with 39 volunteers. We obtained PC operation patterns using a PC logger, sleeping time and activity levels using a wrist-band-type activity tracker, and brain activity and behavior data during a working memory task using optical topography. We also administered two standard questionnaires: the Brief Job Stress Questionnaire (BJS) and the Kessler 6 scale (K6). Supervised machine learning and cross validation were performed. The objective variables were mental scores obtained from the questionnaires and the explanatory variables were the biomarkers obtained from the modalities. Multiple linear regression models for mental scores were comprehensively searched and the optimum models were selected from 2,619,785 candidates. Each mental score estimated with each optimum model was well correlated with each mental score obtained with the questionnaire (correlation coefficient = 0.6-0.8) within a 24% of estimation error. Mental scores obtained by means of questionnaires have been in general use in mental health care for a while, so our multimodality system is potentially useful for mental healthcare due to the quantitative agreement on the mental scores estimated with biomarkers and the mental scores obtained with questionnaires.

show abstract