SNIF-DFA: A Signal Processing and Information Fusion Method for Smart Gua Sha Device
IEEE Sensors Journal
; : 1-1, 2022.
Article
in English
| Scopus | ID: covidwho-2136429
ABSTRACT
Due to the COVID-19 global pandemic, there are more needs 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 paper 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 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. IEEE
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
IEEE Sensors Journal
Year:
2022
Document Type:
Article
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