# Monitoring of [PERSON]'s Disease Based on Wireless Sensing Technology
###### Abstract  
[PERSON]'s disease (HD) is a rare genetic disorder that cannot be cured by current medical techniques. With the development of the disease, the life of patients will become more and more difficult. It is necessary to timely and effectively evaluate the development of the patient's condition based on the patient's clinical symptoms to help doctors to formulate a reasonable and effective treatment plan, alleviate the condition, and improve the quality of life, which reflects humane care. Currently, wearable devices or video surveillance are generally used to monitor the patients, and these schemes have some disadvantages. This paper presents a new method to monitor patients with HD using wireless sensing technology. Firstly, experimental data were collected by the self-developed microwave sensing platform (MSP), and then the data were preprocessed. Finally, support vector machine (SVM) and random forest (RF) algorithms were used to train the model. The MSP system continuously monitors patients in a non-contact way, which will not bring inconvenience to patients' lives, and will not involve privacy issues. The experimental results show that the prediction accuracy of SVM can be as high as 98.0% and that of RF can be as high as 96.7%, which proves the feasibility of the technical scheme described in this paper. HD; MSP; RF; SVM; wireless sensing technology +
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patients are often earlier than or synchronous with abnormal motor symptoms, mainly manifested as depression, often accompanied by insomnia, anorexia, and personality changes. In the later stage, patients will gradually experience hallucinations, delusions, paranoia, and aggressive behavior. HD is characterized by complex clinical symptoms, progressive deterioration of the patient's condition, and usually death 15-20 years after onset [6]. At present, there is no effective treatment for this disease. The purpose of treatment is to improve the quality of life of patients. Several existing treatment methods can be classified as cause treatment and symptomatic treatment [7]. Cause treatment includes direct gene therapy and other indirect molecular therapy, this method cannot be realized at present, but a lot of research has been carried out. The symptomatic treatment is that the doctor obtains the clinical symptoms of the patient through visual observation and other methods and diagnoses the patient's condition against the HD Scale [8], so as to formulate a drug treatment plan to directly alleviate the patient's symptoms. Drug therapy is currently the main treatment for HD. In order to confirm whether drug therapy is effective, doctors need to continue to follow up the effect of drug therapy, so as to improve the treatment. But this treatment has a disadvantage; the doctor's judgment of the patient is mainly based on the naked eye and the HD Scale. The diagnosis result can easily be affected by the subjective consciousness of the doctor. A promising solution is needed to continuously monitor the patient and provide an objective diagnosis basis. At the same time, the mental symptoms of patients are unstable, and patients are prone to hallucinations and aggressive behavior. In order to avoid self-injury, we also need to carry out continuous monitoring and give timely psychotherapy to patients. In order to solve the above-mentioned problems, this paper proposes a new method to monitor HD patients using wireless sensing technology and demonstrates the feasibility of the proposed method. We independently developed the microwave sensing platform (MSP) monitoring tool, which is composed of a transmitter module and a receiver module. It can be directly installed in the indoor environment, without any contact with the patient, and it can be completely monitored in a non-contact way. The working process of MSP is: the transmitting module transmits the wireless signal in C-band, the receiving module receives the wireless signal and extracts the channel state information (CSI) data through channel estimation.