Detecting and differentiating leg bouncing behaviour from everyday movements using tri-axial accelerometer data-Reference-Cited by-同舟云学术

Detecting and differentiating leg bouncing behaviour from everyday movements using tri-axial accelerometer data

Published:2020-09-10 Issue: Volume: Page:
ISSN:
Container-title:Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers
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Author:

Senaratne Hashini¹,Ellis Kisrten¹,Oviatt Sharon¹,Melvin Glenn²

Affiliation:

1. Monash University, Australia

2. Deakin University, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3410530.3414388

Reference21 articles.

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2. Feet Fidgeting Detection Based on Accelerometers Using Decision Tree Learning and Gradient Boosting

3. Gabriel A Koepp Graham K Moore and James A Levine. 2016. Chair-based fidgeting and energy expenditure. BMJ open sport & exercise medicine 2 1 (2016) e000152. Gabriel A Koepp Graham K Moore and James A Levine. 2016. Chair-based fidgeting and energy expenditure. BMJ open sport & exercise medicine 2 1 (2016) e000152.

4. Physical activity classification in free-living conditions using smartphone accelerometer data and exploration of predicted results

5. An automatic user-adapted physical activity classification method using smartphones;Li Pengfei;IEEE Transactions on Biomedical Engineering,2016

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