The global pandemic of the coronavirus disease (COVID-19) is dramatically changing the lives of humans and results in limitation of activities, especially physical activities, which lead to various health issues such as cardiovascular, diabetes, and gout. Physical activities are often viewed as a double-edged sword. On the one hand, it offers enormous health benefits; on the other hand, it can cause irreparable damage to health. Falls during physical activities are a significant cause of fatal and non-fatal injuries. Therefore, continuous monitoring of physical activities is crucial during the quarantine period to detect falls. Even though wearable sensors can detect and recognize human physical activities, in a pandemic crisis, it is not a realistic approach. Smart sensing with the support of smartphones and other wireless devices in a non-contact manner is a promising solution for continuously monitoring physical activities and assisting patients suffering from serious health issues. In this research, a non-contact smart sensing through the walls (TTW) platform is developed to monitor human physical activities during the quarantine period using software-defined radio (SDR) technology. The developed platform is intelligent, flexible, portable, and has multi-functional capabilities. The received orthogonal frequency division multiplexing (OFDM) signals with fine-grained 64-subcarriers wireless channel state information (WCSI) are exploited for classifying different activities by applying machine learning algorithms. The fall activity is classified separately from standing, walking, running, and bending with an accuracy of 99.7% by using a fine tree algorithm. This preliminary smart sensing opens new research directions to detect COVID-19 symptoms and monitor non-communicable and communicable diseases.
Abstract-This paper presents wireless clamp-on torque transducer based on twist angle deformation measurement system using strain gauges. Firstly, the model of a torque measurement system based on the twist angle with strain gauges sensing structure is studied and developed. Secondly, for the system verification, the proposed model is presented as a case study. In this study, both the mechanical and electronics designs are discussed and analyzed. Particularly, using finite element analysis technique the mechanical sensitivity and maximum stresses of the torque sensor are examined. While the readout electronics of the system is verified experimentally by laboratory tests. The torque sensor has the capability of ±50Nm with 0.023 V/Nm of sensitivity under static torque measurement. Finally, the performance of the developed scheme is examined by carrying out simulations followed by experiments. Index Terms-RF wireless telemetry, torque measurement, strain gauges, rotating shaftI.
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