Prosthetic limbs can be controlled directly by the brain, yet are not intelligent enough to perform the functions demanded of them. The main design of the electromechanical parts has evolved over a period of time, but the controllers are yet to be suitably advanced to adapt to the different amputees. Over the period of time many researchers have achieved this by various innovative techniques. With the widespread use of artificial intelligence [especially Genetic Algorithm] and its implementation cost reducing over the years, our goal was primarily to 1) design the mathematical model based on Genetic Algorithm for the intelligent arm, and 2) develop a low cost implementation of the model.
It is increasingly being made aware by various organizations including the WHO (World Health Organization) that Cardiovascular Disease (CVD) is the 'Silent Killer' and is the perhaps the most important cause for death globally in the present times. The prime reason being the fact that CVD often goes unnoticed at the early stages and clinical intervention is soughted only during emergency. A thorough understanding of the nature of the disease reveals the association of physiological abnormalities and subdued physiological disorders that might have raised due to stress, lifestyle related disorders, pathological conditions etc. Studies have revealed that all these problems if addressed to at an early stage can be controlled and the potential risks and hazards lessened to a considerable extent. Early detection is possible in developed countries with expensive and advanced machineries, which can keep the data recorded in a user-friendly device affordable by the patient. But in a developing country like ours a low cost affordable device is yet to be available to the rural population especially addressing the problem. The aim of this study is to design an affordable and reliable Cardiac Health Monitoring platform for identification, data storage and availability to the physician even after a considerable time interval for diagnosis of the condition and post diagnosis continued therapy. The Cardiac Health Monitoring Systems (CHMS) was developed to capture and pre-process physiological parameters (ECG, Heart Sound, Heart Rate in Normal, Stressed and Physiologically abnormal conditions) in real-time and transmit the same using wired as well as wireless communication technology. The CHMS has been so designed is designed to capture the patient's/user's physiological parameters in electrical form e.g. the ECG signal, apply preliminary adaptive filtering to shape the requisite signals and forward the processed data. This data is acquired by Smart hand held mobile device, and the excess processing power of the device is utilized for further processing as well as storage of medical records and transmission of data to the hospital management system or for isolated diagnosis and assessment. Critical readings crossing the set threshold (per WHO standards) would set off an alarm [locally as well as over the mobile network] and thus alert any imminent life-threatening situation.
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