An Enhanced Posture Prediction-Bayesian Network Algorithm for Sleep Posture Recognition in Wireless Body Area Networks

Table 1

Comparative chart of sleep posture recognition.

S. no	Sensor name	No. of subjects	No. of sensors	Algorithm	Accuracy rate	Year of work
1	Uniformly distributed pressure sensors	10	1768	Support vector machines	77.14%	2015
2	Uniformly distributed FSR sensor	19	3200	Deep neural networks	99.70%	2018
3	Matrix of FSR sensors	6	NA	Template matching by a minimum mean squared error	96.10%	2017
4	Uniformly distributed pressure sensors	12	1728	Fully connected networks	97.90%	2020
5	Uniformly distributed pressure sensors	19	3200	Deep neural networks	97.10%	2018
6	Uniformly distributed pressure sensors	14	8192	EMD+-nearest neighborhood	91.21%	2016
7	Uniformly distributed pressure sensors	16	1024	ResNet	90.08%	2021
8	Accelerometer pulse sensor (our method)	14	5	Posture prediction-Bayesian network (PP-BN)	91.05%	2022