Virtual Reality Therapy and Machine Learning Techniques in Drug Addiction Treatment

With the continuous development of machine learning technology, machine learning methods have broad application prospects in medical data mining. This paper proposes a method of using virtual reality technology to assist drug addiction treatments with a sample size of 58 drug abusers in a drug rehabilitation center located in Zhejiang province, China. In the process of drug addicts watching VR videos in different scenes, physiological data of concentration and heart rate are collected. A hybrid machine learning technique that combines principal component analysis (PCA) and K-Means++ clustering algorithm is used to cluster drug addicts to find out the relationship between cardiac physiological characteristic data and treatment effect. The experimental results show that after VR treatment, the mean and standard deviation heart rate of the patients have decreased significantly, which provides a firm evidence that the patient's response to drug stimulation is severely reduced after VR treatments. The conclusion was drawn that the virtual reality is indeed effective in assisting detoxification.