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Stroke affects 15 million people worldwide each year, leading to huge medical expenditures in death, disability and patient monitoring
.
Stroke usually leads to hemiplegia, that is, hemiplegia, which seriously affects the movement and coordination of the upper limbs
Thrombotic stroke
Therefore, an automatic scoring system for hemiplegia independent of continuous professional medical care has important research significance in acute stroke
.
Accelerometers can be used to quantify the upper limb usage of hemiplegic patients after stroke, using activity counts, and the upper limb usage of hemiplegic patients is lower than that of healthy patients
Experimental flowchart
NIHSS is a scale that is used as the clinical gold standard for measuring the severity of stroke
.
The training consists of different stages, including raising the arm, keeping it level for a period of time, and then placing the arm in a resting position
diagnosis
Use two low-cost wearable wristband sensors and a three-axis accelerometer from Eoxys to collect data
.
The accelerometer collects data at a full-scale range with a sampling rate of 100 Hz
Statistical significance of changes in AUCs between the control group and stroke
From the statistical analysis of the characteristics, it can be seen that the control group is easily separated from stroke patients with hemiplegia, which is very clinically obvious
.
Patients with moderate and severe hemiplegia have low spontaneous movements, but patients with moderate hemiplegia can try to perform the indicated exercises
Future research in this area includes the use of multiple sensors and different modes to accurately determine the severity of hemiplegia at each level of the clinical gold standard
.
.
S.
S.
Datta, CK Karmakar, AS Rao, B.
Yan and M.
Palaniswami, " Automated Scoring of Hemiparesis in Acute Stroke From Measures of Upper Limb Co-Ordination Using Wearable Accelerometry ," inAutomated Scoring of Hemiparesis in Acute Stroke From Measures of Limb Co-Ordination the Using Upper Wearable accelerometry the IEEE Transactions oN Neural Systems and Rehabilitation Engineering in this message