The prototype of wearable sensors system for supervision of patient rehabilitation using artificial intelligence methods

The Role of Artificial Intelligence in Future Rehabilitation Services: A Systematic Literature Review

“…Logistic regression is considered the baseline supervised machine learning algorithm to classify an observation, and its outputs can be easily interpreted as probabilities of the occurrence of a class [71]. In the case where authors handled multiple classes [56], a generalization of logistic regression was used: the softmax regression algorithm [72]. A more simplest approach used to make class-probability inference was the NB algorithm.…”

“…Participants with different neurological and orthopedic conditions (N=41) [50] Upper limb rehabilitation in stroke Upper limb goal directed ADL tasks to train, strength, ROM, functional capacity Stroke (N=20); healthy subjects (N=10) Healthy subject(N=17) [56] Physical activity Squat Healthy subject(N=4) [57] Shoulder rehabilitation Shoulder flexion Healthy subject(N=1) [58] Upper limb rehabilitation in stroke Functional upper limb movements Stroke (N=23); Healthy subjects (N=4) [59] Knee rehabilitation Standing hamstring curl, straight leg raise exercises Knee osteoarthritis (N=8) Track shoulder physiotherapy participation using inertial data collected in an unobtrusive and easyto-use way…”

“…Moreover, IMUs coupled with different sensors such as optical fiber sensors [28] and flex and force resistive sensors [34] are useful to acquire more information about the amount of deflection or bending and the force applied during a rehabilitation task. Acceleration signals were also used coupled to electrocardiogram (ECG) data in order to better recognize the patient's physical activity form [56].…”

“…Machine learning algorithms address activity recognition tasks aimed to identify specific rehabilitation actions to remotely track patients' adherence to the prescribed therapy and sometimes to measure the treatment outcomes based on patients' activity in real-world life [85]. Most of the reviewed papers covered the problem of recognizing activities for specific body parts like strength training exercises for upper and lower limb [29,41,44,56], exercise to improve range of motion [38], flexibility and balance exercises [37,44], specific rehabilitation exercise for upper limb and lower impaired limb in stroke [31,40,55], and shoulder impairments [32,45,52]. Other articles monitored activities of daily living (ADL), detecting general activities such as standing, sitting, squatting, walking, and running useful for health promotion programs in the elderly [28,44], and other routine activities involving upper limb goal-directed tasks in stroke rehabilitation [50].…”