Parkinson's disease resting state tremor assessment method based on wearable somatosensory net

Abstract

The invention discloses a Parkinson's disease resting state tremor assessment method based on a wearable somatosensory net, belongs to the field of wireless sensor networks and data analysis thereof,and particularly relates to a method for obtaining and identifying the arm tremor state of a Parkinson's disease patient on the basis of the wearable somatosensory net. The attitude angle of the upperarm, the attitude angle of the lower arm and the attitude angle of the wrist are measured to calculate the angle change amount of the elbow joint and the angle change amount of the wrist joint, the characteristics of the angle change amount are extracted, the real-time characteristics of an electromyographic signal are extracted, a hidden Markov model is trained according to characteristic data and a UPDRS (Unified Parkinson's Disease Rating Scale), and a current optimal state sequence is output. The method can provide technical support for evaluating the arm tremor degree of the Parkinson'sdisease patient, and a theoretical foundation is provided for crowds who include Parkinson's disease patients, old people, weak people and the like and need to know the occurrence of the early-phase Parkinson's disease in time.

Description

technical field [0001] The invention relates to the field of wireless sensor networks and data analysis thereof, in particular to a method for evaluating Parkinson's resting state tremor based on a wearable somatosensory network. Background technique [0002] Parkinson's disease is a degenerative disorder of the central nervous system that is characterized by varying degrees of impairment of motor physical abilities. It is more common in older adults, with most cases occurring after the age of 50. Parkinson's disease mainly affects four areas of motor function, including bradykinesia, resting tremor, limb stiffness and postural instability. Rest tremor is more prominent in the upper limbs, and this tremor will gradually spread from one side to both sides, and the condition will gradually increase. Therefore, early identification of rest tremor in daily life is very necessary. [0003] Applying wearable sensors to early tremor assessment is a current research hotspot in ac...

AI Technical Summary

Problems solved by technology

[0006] Purpose of the invention: The present invention proposes a wearable somatosensory network-based evaluation method for Parkinson's patient's arm tremor in the resting state, to achieve accurate identification of the degree of arm tremor in daily activities, and to solve the following technical problem: the patient's daily behavior affects the state of arm tremor The recognition results of the system reduce the correct detection rate of the system; the degree of tremor in the early stage is relatively slight, and it is easy to be mistaken for environmental noise, so it cannot be accurately recognized

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