Title: Research on recognition of human lying posture based on neural network

Authors: Qi Wang; Xianyu Meng; Cong Li; Hongsheng Liu; Xiquan Yu

Addresses: Changchun University of Science and Technology, No. 7089, Weixing Road, Jilin Province, ChangChun, 130000, China ' Changchun University of Science and Technology, No. 7089, Weixing Road, Jilin Province, ChangChun, 130000, China ' Changchun University of Science and Technology, No. 7089, Weixing Road, Jilin Province, ChangChun, 130000, China ' Changchun University of Science and Technology, No. 7089, Weixing Road, Jilin Province, ChangChun, 130000, China ' Changchun University of Science and Technology, No. 7089, Weixing Road, Jilin Province, ChangChun, 130000, China

Abstract: As a high-tech intelligent product, the intelligent nursing bed largely meets the needs of the disabled for self-care, and saves a lot of manpower and material resources. In order to improve the safety and reliability of the intelligent nursing bed and ensure the safety of the user, this paper adds the recognition of the human body's lying position as a part of the movement signal of the nursing bed. The Kinect sensor is used to track human bones, record human bone data, and preprocess human bone data. Use the pattern recognition toolbox in Matlab to classify the processed data to realise the recognition of the human body's lying posture. The average recognition rate of the five postures is 98.1%. The results show that the model used in this experiment has a high degree of recognition and can greatly improve the safety and reliability of the intelligent nursing bed.

Keywords: intelligent nursing bed; lying position recognition; Kinect sensor; bone data; neural network.

DOI: 10.1504/IJNM.2021.126675

International Journal of Nanomanufacturing, 2021 Vol.17 No.3/4, pp.167 - 179

Received: 24 Mar 2021
Accepted: 24 Feb 2022
Published online: 01 Nov 2022 *

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