Pervasive_Health_2020-26.pdf (8.57 MB)
Multimodal fusion of IMUs and EPS body-worn sensors for scratch recognition
conference contribution
posted on 2023-06-09, 20:51 authored by Zygimantas Jocys, Arash Pour Yazdan Panah Kermani, Daniel RoggenDaniel RoggenIn order to develop and evaluate the extent to which itching affects a person's daily life, it is useful to develop automated means to recognise the action of scratching. We present an investigation of sensors and algorithms to realise a wearable scratch detection device. We collected a dataset, where each user wore 4 inertial measurement unit (IMU) sensors and one electric potential sensor (EPS). Data were collected from nine users, where each user followed a 40-min protocol, which involved scratching different parts of head, shoulder, and leg, as well as other activities such as walking, drinking water, brushing teeth, and typing to a computer. The dataset contained 813 scratching instances and 5 h 15 min of recorded data. We investigated the trade-offs between the number of devices worn (comfort) and accuracy. We trained the k-NN and random forest algorithms by using between 1 and 5 features per channel. We concluded that a scratch could be detected with 80.7% accuracy by using the random forest algorithm on hand coordinates, which required four devices. However, an f1 score of 70% could be achieved with k-NN with IMU and EPS data, which only required one device. Moreover, the fusion of IMU data with EPS data improved the accuracy and reduced the deviation between the folds. This expanded the state-of-the-art method by opening up new trade-offs between accuracy and comfort for future research
Funding
Automated recognition of hair touch and scalp scratching through novel sensing modalities, sensor fusion and machine learning approaches; G2738; UNILEVER; MA-2017-02004N
History
Publication status
- Published
File Version
- Accepted version
Journal
PervasiveHealth '20: Proceedings of the 14th EAI International Conference on Pervasive Computing Technologies for HealthcarePublisher
Association for Computing MachineryExternal DOI
Page range
325-335Event name
EAI PervasiveHealth 2020 - 14th EAI International Conference on Pervasive Computing Technologies for HealthcareEvent location
Atlanta, United StatesEvent type
conferenceEvent date
October 6-8, 2020Place of publication
New York, NY, United StatesISBN
9781450375320Department affiliated with
- Engineering and Design Publications
Research groups affiliated with
- Sensor Technology Research Centre Publications
Full text available
- Yes
Peer reviewed?
- Yes
Editors
Lana Yarosh, Maia Jacobs, Junehwa Song, Jakob Badram, Kellie Morrisey, Chia-Fang Chung, Rita OrjiLegacy Posted Date
2020-03-13First Open Access (FOA) Date
2021-02-10First Compliant Deposit (FCD) Date
2020-03-12Usage metrics
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