An Efficient Multi-sensor Positions Human Activity Recognition: Elderly Peoples in Rural Areas in Focus

Author:

Abdu HarunaORCID,Noor Mohd Halim Mohd,Abdullah Rosni

Publisher

Springer International Publishing

Reference28 articles.

1. UN DESA’s Population Division, World Population Ageing 2019 (2019)

2. Woznowski, P.R., King, R., Harwin, W., Craddock, I.: A human activity Recognition framework for healthcare applications: Ontology, labelling strategies, and best practice. In: IoTBD 2016 – Proceedings of International Conference Internet Things Big Data, no. IoTBD, pp. 369–377 (2016)

3. Wang, Z., Meng, F., Yuan, G., Yan, Q., Xia, S.: An overview of human activity recognition based on smartphone. Sensor Rev. (2018)

4. Noor, M.H.M., Salcic, Z., Wang, K.I.K.: Adaptive sliding window segmentation for physical activity recognition using a single tri-axial accelerometer. Pervasive Mob. Comput. 38, 41–59 (2017)

5. Wang, X., Kim, H.: Detecting user activities with the accelerometer on android smartphones. J. Multimed. Inf. Syst. 2(2), 233–240 (2015)

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1. Implementation and Layout Optimization of Motion Sensor for Anomaly Detection in Daily Life of Elderly Persons;2021 13th International Conference on Information & Communication Technology and System (ICTS);2021-10-20

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