Saeed Vahedi, Mareft Siah Koohian, Milad Rahati, Negar Rostami, Elaheh Fallahzadeh, Roghayeh Afrondeh,
Volume 20, Issue 23 (9-2022)
Abstract
Covid 19 disease is associated with a wide range of clinical symptoms and long-term complications. For most sports medicine professionals, it's a new challenge for people to resume their previous activities after recovering from Covid 19 after receiving the exercise prescription and care. The aim of this study was to review the appropriate physical activity for those recovering from Covid 19 infection based on the type of involvement they developed during the illness. For this study, a review study method was selected. This is done in three steps. In the first stage, physical activity in Quid, in the second stage, organ involvement in Quid, and in the third stage, sports prescriptions in organ involvement by searching for appropriate keywords in reputable scientific databases such as Pubmed, ACSM, SID. ir and Science Direct were searched, content related to the purpose of the articles were extracted and collected and analyzed for content. Examination of organs after recovery from Covid 19 infection is essential to return to physical activity. Physical activity prescriptions in those recovering from Corona varies from disease to patient, and organ to organ. Exercising in Covid conditions requires consideration. The cardiovascular, respiratory, blood, gastrointestinal, and musculoskeletal systems are affected by Covid 19 infection. Exercise, on the other hand, has different effects on the immune system depending on its severity, and the immune system undergoes changes in Covid 19 disease. The type, intensity, and duration of exercise or physical activity vary according to the patient and the symptoms or side effects left by Quid, and the readiness of the various organs for physical activity should be assessed.
Saeed Mollahoseini Paghale, Milad Fallahzade, Mohammadreza Amirseyfadini,
Volume 23, Issue 30 (1-2026)
Abstract
Background and Aims: Controlling hand tremors in neurological disorders like Parkinson's has gotten a lot of attention in recent decades. The number of theories about closed-loop deep brain stimulation is rapidly growing. The goal of this work is to offer a machine learning-based automated closed loop system for the rehabilitation of Parkinson's patients with hand tremor symptoms.
Materials and Methods: In the current study, vibration was simulated using a mathematical model that included a muscle model, basal ganglia, cortex, and supplementary motor area. To manage hand tremor, the non-integer PID proportional controller, as well as the intelligent Proximal Policy Optimization (PPO) algorithm as a subset of reinforcement learning, are employed to adapt the coefficients.
Results: One of the advantages of the proposed method, aside from reducing hand tremor and automatic learning to use at various levels of the disease, which has yielded acceptable results when compared to other control methods, is its practical implementation in the real world due to the simplicity of the controller. The automatic adjustment of artificial intelligence network coefficients in the presented strategy (PPO) makes it simple to create intelligent system.
Conclusion: The proposed intelligent system significantly reduces the side effects of continuous brain stimulation in the open-loop manner stimulation, in addition to optimizing output signals such as hand tremor compared to other controllers and being usable for all levels of the disease due to its adaptability.
