Reliability and Validity of a Wearable Sensing System and Online Gait Analysis Report in Persons after Stroke

Abstract

The restoration of gait and mobility after stroke is an important and challenging therapy goal due to the complexity of the potentially impaired functions. As a result, precise and clinically feasible assessment methods are required for personalized gait rehabilitation after stroke. The aim of this study is to investigate the reliability and validity of a sensor-based gait analysis system in stroke survivors with different severities of gait deficits. For this purpose, 28 chronic stroke survivors (9 women, ages: 62.04 ± 11.68 years) with mild to moderate walking impairments performed a set of ambulatory assessments (3× 10MWT, 1× 6MWT per session) twice while being equipped with a sensor suit. The derived gait reports provided information about speed, step length, step width, swing and stance phases, as well as joint angles of the hip, knee, and ankle, which we analyzed for test-retest reliability and hypothesis testing. Further, test-retest reliability resulted in a mean ICC of 0.78 (range: 0.46–0.88) for walking 10 m and a mean ICC of 0.90 (range: 0.63–0.99) for walking 6 min. Additionally, all gait parameters showed moderate-to-strong correlations with clinical scales reflecting lower limb function. These results support the applicability of this sensor-based gait analysis system for individuals with stroke-related walking impairments.

Dual Tasking Affects the Outcomes of Instrumented Timed up and Go, Sit-to-Stand, Balance, and 10-Meter Walk Tests in Stroke Survivors

“…Another reason for utilizing such a motion capture system was due to its portability. This motion capture system has been validated and widely used for capturing detailed body motion in out-of-lab scenarios [39][40][41]. A total of 8 IMUs were strategically positioned on various body segments, including the feet, shanks, thighs, sternum, and sacrum of each participant.…”

Machine Learning Classification for a Second Opinion System in the Selection of Assistive Technology in Post-Stroke Patients

“…Currently, standardized clinical measures for profiling movement deficits in post-stroke patients are subjective and imprecise [11]. The future of research in the area of assistive technologies design lies in the increased use of robotic devices, personalised by 3D printing; Internet of Things wearable sensors for personalised training of limb use, gait and balance, and activities of daily living and health monitoring [17][18][19][20][21]; and even novel brain-computer interfaces [22,23] and associated computational models [24]. Further, more advanced studies may additionally use data from postural and gait analysis [25,26].…”

Inertial Measurement Units to evaluate the efficacity of Equino Varus Foot surgery in post stroke hemiparetic patients

“…The parameters used have proved highly effective in the longitudinal follow-up of patients suffering from neurological diseases such as Multiple Sclerosis or Parkinsons disease [14][15][16][17]. In post stroke patients, several parameters have shown good reliability [18][19][20]. However, IMUs have never been used in post-operative evaluation in this population.…”