Executive Summary : | Skeletal Muscle is an important tissue for human health and well-being. Skeletal muscle is the largest body compartment in most adults. It is the main determinant of global muscle metabolic function, strength, and physical performance. For a healthier adult, the protein level should be 6.4-8.3 g/dL. The skeletal muscle mass deficiency results in lowering of protein level thereby leading to Sarcopenia disease. The Sarcopenia spectrum includes sarcopenic obesity, frailty, and cachexia that collectively have in common loss of skeletal muscle mass and functional abnormalities, including weakness and limited physical performance. Moreover, earlier detection of Sarcopenia eliminates the adverse effects of metabolism such as diabetes, depression, lipid level abnormalities, and weight gain. The adverse outcomes are pathological bone fractures and even death. Sarcopenia leads to osteoporosis, metabolic syndrome and difficulty in performing day-to-day activities. The major drawback of existing methods in detecting Sarcopenia is that it involves exposure to radiations. At present, Dual-energy X-ray absorptiometry (DXA) measures muscle mass with few limitations. They are variations in measurements according to the region under investigation, irregularities in hydration status, and low precision in tall and obese persons. These limitations are due to the low dosage level of X-ray radiations in certain muscle regions of the human body such as the heart, head, lower and upper extremities. Nevertheless, the values obtained from the DXA and calculations need to await further confirmation. The objective of the proposal is to design and develop a non-invasive passive flexible UWB patch antenna sensor for diagnosing protein loss through human muscle mass measurement. The proposed methodology can be developed as a product through the MATLAB App compatible with Android devices. The non-invasive passive flexible Ultra Wide Band (UWB)Myogram antenna sensor is adhesively fixed on the ventral surface of forearm and biceps for the measurement of skeletal and lean mass respectively. The proposed antenna sensor performs electromagnetic energy absorption from muscle tissues under radiating near-field conditions. The muscle tissue signal from the antenna is applied to blind source filtering-Non-negative Matrix Factorization (NMF) that segregate muscle fiber signal and fat signal. The output from NMF is then subjected to Multi-Synchro Squeezing Transform (MSST) to generate the concentrated Time-Frequency representation for a strongly time-varying signal and finally correlated using a linear regression machine-learning algorithm to diagnose Sarcopenia. The novelty is that this proposal attempts to measure the protein of a human being: By a Non-invasive method, Without going to the lab to give a blood sample, The subject is not exposed to any kind of radiation, No Processing time for viewing the result. |