Body responses towards a morning walk in a tropical city

Francisco Benita; Garvit Bansal; Darshan Virupaksha; Francesco Scandola; Bige Tunçer

doi:10.1080/01426397.2020.1808956

Body responses towards a morning walk in a tropical city

Francisco Benita (Corresponding author)
, Garvit Bansal
, Darshan Virupaksha
, Francesco Scandola
, Bige Tunçer

Research output: Contribution to journal › Article › Academic › peer-review

5 Citations (Scopus)

Abstract

The purpose of this study is to present an exploratory analysis of the relationship between body responses, immediate environmental factors and stress-related events. Using an experimental setup for data collection and information fusion from wearable sensors, this work tests three Machine Learning Algorithms for supervised classification of stress detection. Body skin temperature and electrodermal activity are processed to identify patterns of stress reaction while walking. Immediate environmental features from continuous sensor data are found to be useful in identifying stress-related events. The experiment was carried out in Singapore, a city-state with hot tropical weather where the climate conditions of the city encourage urban planners to meet walkability needs of the residents as well as to ensure short walking trips.

Original language	English
Pages (from-to)	966-983
Number of pages	18
Journal	Landscape Research
Volume	45
Issue number	8
DOIs	https://doi.org/10.1080/01426397.2020.1808956
Publication status	Published - 16 Nov 2020
Externally published	Yes

Funding

The research leading to these results is supported by funding from the National Research Foundation, Prime Minister’s Office, Singapore, under its Grant RGNRF1402; National Research Foundation Singapore [RGNRF1402]; The authors are grateful to two anonymous referees for helpful suggestions and comments.

Keywords

Stress, walkability, tropical weather outdoor comfort, interpretable features, Singapore

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10.1080/01426397.2020.1808956

Cite this

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AU - Virupaksha, Darshan

AU - Scandola, Francesco

AU - Tunçer, Bige

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AB - The purpose of this study is to present an exploratory analysis of the relationship between body responses, immediate environmental factors and stress-related events. Using an experimental setup for data collection and information fusion from wearable sensors, this work tests three Machine Learning Algorithms for supervised classification of stress detection. Body skin temperature and electrodermal activity are processed to identify patterns of stress reaction while walking. Immediate environmental features from continuous sensor data are found to be useful in identifying stress-related events. The experiment was carried out in Singapore, a city-state with hot tropical weather where the climate conditions of the city encourage urban planners to meet walkability needs of the residents as well as to ensure short walking trips.

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Body responses towards a morning walk in a tropical city

Abstract

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Keywords

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