中风后康复装置

Naveed Shahzad
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引用次数: 0

摘要

中风是一种医学疾病,是第五大死亡原因,也是导致残疾的主要原因。中风的不同原因有血压高、肥胖、吸烟等,只有通过规律的物理治疗和患者的意志力才能加快康复。常规物理治疗可能因患者的其他任务或医生的没空而中断。这可能会导致恢复过程的延迟。因此,需要努力解决这个问题。该装置可用于监测和执行医生建议的选定运动。这里我们的重点是右上肢,因为它是最常见的受影响的区域。此外,还设计了android应用程序,为医生和病人提供不同的控制台。病人的应用程序显示病人的历史和进展,而医生设置时间,也可以看到进展。首先,该装置跟踪手指和手腕的运动以及正在锻炼的肌肉的信号强度,然后执行肢体的辅助屈伸操作。结果通过图形显示在应用程序中,以便患者和医生都可以监控进展。因此,这种设计给病人和医生都带来了方便。随着世界向智能设备和远程监控的转变,有必要在卫生部门应用现代技术,使用物联网平台,某些医疗可以让医生更容易,对患者更有效。通过使用不同的传感器,微控制器,Arduino软件,移动应用程序,可以监控,记录和辅助患者的物理治疗练习。
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POST STROKE REHABILITATION DEVICE
Stroke is a medical condition that is the fifth cause of death and a leading cause of disability. The different reasons for stroke are high B.P, obesity, smoking, etc. recovery can only be sped up by regular physiotherapy and willpower of the patient. Regular physiotherapy can be interrupted by other commitments of the patient or by the doctor's unavailability. This may lead to a delay in the recovery process. Therefore, the efforts are needed to tackle the problem. The proposed device can be used to monitor and carry out selected exercises advised by the doctor. Here the upper right limb is our focus because it is the most common area to be affected. Furthermore, android application is also designed which have different consoles for doctor and patient. The patient’s app shows the history and progress of the patient while the doctor sets the time and can also see the progress. Firstly, the unit tracks finger and wrist movements and the signal strength of the muscles being exercised, and then performs assisted flexion / extension manipulation of the limb. The results are shown in the app using the graphs so that the patient and the doctor can both monitor the progress. Thus, this design gives ease to the patient as well as the doctor. With the world shifting towards smart devices and remote monitoring and control, there is a need to apply modern technology in the health dept. using the platform of IOT, certain medical treatments can be made easier for the doctors and effective for the patients. By using different sensors, a microcontroller, Arduino software, mobile application, the patient’s physiotherapy exercises can be monitored, recorded and assisted.
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