Utilizing a 5G spectrum for health care to detect the tremors and breathing activity for multiple sclerosis

Abstract

Utilizing fifth‐generation (5G) sensing in the health care sector with increased capacity and massive spectrum range increases the quality of health care monitoring systems. In this paper, 5G C‐band sensing operating at 4.8 GHz is used to monitor a particular body motion of multiple sclerosis patients, especially the tremors and breathing patterns. The breathing pattern obtained using 5G C‐band technology is compared with the invasive breathing sensor to monitor the subtle chest movements caused due to respiration. The 5G C‐band has a huge spectrum from 1 to 100 GHz, which enhances the capacity and performance of wireless communication by increasing the data rate from 20 Gb/s to 1 Tb/s. The system captures and monitors the wireless channel information of different body motions and efficiently identifies the tremors experienced since each body motion induces a unique imprint that is used for a particular purpose. Different machine learning algorithms such as support vector machine, k‐nearest neighbors, and random forest are used to classify the wireless channel information data obtained for various human activities. The values obtained using different machine learning algorithms for various performance metrics such as accuracy, precision, recall, specificity, Kappa, and F‐measure indicate that the proposed method can efficiently identify the particular conditions experienced by multiple sclerosis patients.

A Review of the State of the Art in Non-Contact Sensing for COVID-19

“…The use of radio frequency (RF) signal sensing can detect the vital signs of individuals by sensing the minute movements of the chest made while breathing as the heart beats ( [ 73 , 79 , 80 , 81 , 82 ]). This technique can be used for monitoring the vital signs of patients independent of their activities [ 83 ].…”

RF Sensing Technologies for Assisted Daily Living in Healthcare: A Comprehensive Review

“…The amplitude and sanitized phase information of selected subcarrier(s) are then classified using machine learning techniques to classify different body movements [54] [55].…”

A Systematic Review of Non-Contact Sensing for Developing a Platform to Contain COVID-19

“…A particular body movement of multiple sclerosis patients is monitored by a C-band sensing system working at 4.8 GHz, and especially the tremors and breathing patterns by a 5 G potential band. This system can identify the particular condition of a patient efficiently [ 70 ]. The wireless signal technology successfully detects human motions and related diseases in a non-contact manner [ 71 ].…”