SNIF-DFA: A Signal Processing and Information Fusion Method for Smart Gua Sha Device

Due to the COVID-19 global pandemic, there is more need for remote patient care, especially in rehabilitation requiring direct contact. However, traditional Chinese rehabilitation technologies, such as gua sha, often need to be implemented by well-trained professionals. To automate and professionalize gua sha, it is necessary to record the nursing and rehabilitation process and reproduce the process in developing smart gua sha equipment. This article proposes a new signal processing and sensor fusion method for developing a piece of smart gua sha equipment. A novel stabilized numerical integration method based on information fusion and detrended fluctuation analysis (SNIF-DFA) is performed to obtain the velocity and displacement information during the gua sha operation. The experimental results show that the proposed method outperforms the traditional numerical integration method with respect to information accuracy and realizes accurate position calculations. This is of great significance in developing robots or automated machines that reproduce the nursing and rehabilitation operations of medical professionals.

Automated summary

Due to the COVID-19 pandemic, the demand for remote patient care, especially in rehabilitation requiring direct contact, has increased. Traditional Chinese rehabilitation technologies, such as gua sha, usually require well-trained professionals to perform. To automate and professionalize gua sha, it is necessary to record the nursing and rehabilitation process and replicate it through the development of smart gua sha equipment. This article proposes a new signal processing and sensor fusion method for developing smart gua sha equipment, and experimental results show its superiority over traditional methods.