Bayesian network aided grasp and grip efficiency estimation using a smart data glove for post-stroke diagnosis

The early warning research on nursing care of stroke patients with intelligent wearable devices under COVID-19

“…The results show that the patient has good compliance, and by collecting simple data from the accelerometer, the activity ratio of the affected and non-affected upper limbs can be assessed, and clinically relevant information about the movement status of the upper limbs can be collected. The literature [ 12 ] indicated that the use of an accelerometer placed on the arm can obtain an accurate estimate of upper limb function. Moreover, the author used a small part of the tasks from the Wolf Functional Ability Scale (FAS) to obtain the FAS total score through data analysis.…”

Finger Bending Sensing Based on Series-Connected Fiber Bragg Gratings

“…Finger motion was accurately measured by using multiple IMU inertial measurement unit sensors and control algorithms. Debeshi Dutta et al [ 7 ] proposed a smart glove to provide timely estimation of grasp quality for better treatment of stroke patients. Moe Amanzadeh et al [ 8 ] have presented a comprehensive critical review of the evolution trend and sensing principles of technologies used in the development of fiber optic shape sensors.…”