医学
步态
可穿戴计算机
物理医学与康复
平衡(能力)
计算机科学
嵌入式系统
作者
Zawar Khan Khattak,Xin Jiao,Tianyi Hu,Qineng Shao,Xin Sun,Xin Zhao,Dongyun Gu
标识
DOI:10.1016/j.spinee.2023.03.004
摘要
Background Context Cervical spondylotic myelopathy (CSM) is a degenerative disease caused by cervical cord compression and can lead to the significant impairment of motor function including gait and balance disturbances and changes in lower extremity muscle activity. Purpose This study aimed to characterize gait, balance and lower extremity muscle activity in patients with CSM compared to age-matched healthy controls (HCs) using wearable sensors in the clinical setting. Study Design Nonrandomized, prospective cohort study. Patient Sample Ten CSM patients and 10 age-matched HCs were recruited for this study. Outcome Measures Gait and balance function parameters contained spatial temporal parameters, step regularity (SR1), stride regularity (SR2) and harmonic ratio (HR). EMG muscle activity parameters included time to peak and peak value during loading, stance, and swing phase. Methods In this study, parameters of gait and balance function were extracted using triaxial accelerometer attached to the spinous processes of Lumbar 5 while participants performed an overground walking at a self-preferred speed. Moreover, muscular activity was simultaneously recorded via sEMG sensors attached to tibialis anterior (TA), rectus femoris (RF), bicep femoris (BF), and gastrocnemius lateral (GL). Independent sample t test was used to find the differences between CSM patients and HCs. Results Gait analysis showed cadence, step length and walking speed were statistically significantly lower in CSM patients than HCs. Stride time was significantly higher for CSM patients in comparison to HCs. Lower root mean square ratio (RMSR) of acceleration in the mediolateral (ML) direction, HR in the anteroposterior (AP) direction, SR1 in the AP direction and SR2 in all three directions were observed in CSM patients. For muscle activity analysis, EMG RMS for TA and RF during loading phase and RMS for GL during midstance phase was significantly lower for CSM patients, while significantly higher value was observed for RF RMS during midstance phase and GL RMS during swing phase in CSM patients. Conclusion Our pilot study shows that wearable sensors are able to detect the changes of gait, balance and lower extremity muscle activities of CSM patients in the clinical setting. This pilot study sets the stage for future researches on the diagnosis and monitor progression of CSM disease using wearable technology.
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