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Journal of Intelligent Computing
 

Use of Accelerometer Sensors for Monitoring the Health Status of Disabled People
Ivo Draganov, Pavel Dinev, Darko Brodi, Ognian Boumbarov
Faculty of Telecommunications, Technical University of Sofia, 8 Kl Ohridski Blvd, Sofia 1000, Bulgaria., Technical Faculty in Bor, V.J. 12, 19210 Bor, Serbia
Abstract: Patients with disabilities and their health status detection is significant in the intelligent computing. When there is no health support people for the disabled people, a system using accelerometer sensors is able to monitor the conditions. While we use the KNN classifier after raw data pre-processing, we have identified six modes of activities. We are able to draw incredible data results which can bring useful data analysis of the observation and detection of the health status of the observed disabled people for a longer time.
Keywords: Human Activity Recognition, Accelerometer, k-NN, Patient, Motor Disabilities Use of Accelerometer Sensors for Monitoring the Health Status of Disabled People
DOI:https://doi.org/10.6025/jic/2021/12/1/1-7
Full_Text   PDF 403 KB   Download:   384  times
References:

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[8] Bayat, A., Pomlun, M., Tran, D. (2014). A study on Human Activity Recognition Using Accelerometer Data From Smartphones, Procedia Computer Science, 34, p 450-457, 2014.
[9] Kwon, Y., Kang, K., Bae, C. (2014). Unsupervised Learning for Human Activity Recognition Using Smartphone Sensors, Expert Systems with Applications, 41(14), p 6067- 6074, 2014.
[10] Duong, T., Phung, D., Bui, H., Venkatesh, S. (2009). Efficient Duration and Hierarchical Modeling for Human Activity Recognition, Artificial Intelligence, 173 (7-8), p 830- 856, 2009.
[11] Weiss, G., Lockhart, J. (2012). The Impact of Personalization on Smartphone-Based Activity Recognition, AAAI Workshop on Activity Context Representation: Techniques and Languages, p 98-104, 2012.
[12] http://www.cis.fordham.edu/wisdm/dataset.php


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