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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/69399

    Title: 應用皮質肌肉協調性評估腦中風患者復健後之功能恢復情況;Using Cortico-muscular coherence to evaluate the functional recovery of stroke patients in response to rehabilitation
    Authors: 郭士豪;Kuo,Shih-hao
    Contributors: 生物醫學工程研究所
    Keywords: 皮質肌肉協調性;中風;復健機制;cortico-muscular coherence;stroke;rehabilitation
    Date: 2016-01-28
    Issue Date: 2016-03-17 20:24:59 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 本研究目的在於藉由收取腦中風患者復健前後測的腦波訊號與肌電訊號後計算皮質肌肉協調性(Cortico-muscular Coherence;CMC),並結合現行復健上所使用的三種上肢運動功能量表(FMA、TEMPA與WMFT)來探討腦中風患者接受傳統復健和虛擬實境復健後大腦調控上肢手臂肌肉運動的情形。
    本研究中共收取了17位受試者(男性:12;女性:5),平均年齡59.59±12.10歲,其中7人接受現行復健,10人接受虛擬實境復健。兩組受試者復健的療程原則上都為一周四次,一次一小時,並在六個星期內完成復健訓練療程。每位受試者進行復健前與復健後皆會進行運動評估測驗,測驗任務皆為執行上肢肩關節前屈(Shoulder Flexion)與上肢肩關節伸直(Shoulder Extension)的運動任務,並量測運動中的EEG與EMG訊號。將EEG與EMG訊號進行前處理與分段處理後計算皮質肌肉協調性並結合三種量表分數進步率進行迴歸分析。結果顯示兩組患者進行復健後只在WMFT量表分數增益與進步率上達到顯著進步,表示評估量表可能在不同復健方式的組群無法得到客觀的結果,在腦波頻譜分析中,可以發現復健後在α與β頻帶上9個電極位置FMA量表分數進步率越高,能量進步率越低,而在γ頻帶上,F3、C3、C4與P3電極位置FMA進步率越高,功率能量變化率越高,而其他電極位置則是FMA進步率越高,功率能量變化率越低趨勢,觀察到α頻帶F3、C3與P4和β頻帶F3、F4、C3與C4還有γ頻帶F3、F4、C3、C4、P3與P4電極位置TEMPA進步率越高,功率能量變化率越高的趨勢,但都未達到顯著性,此外三個頻帶上也發現9個電極位置WMFT量表分數進步率越高,能量進步率越低,也沒有達到顯著。CMC與量表分數進步率上發現斜方肌、前三角肌、中三角肌、後三角肌與肱二頭肌的C3-CMC在 FMA進步率越高,CMC變化率也越高,則表示接受復健後提升受傷腦區活化有助於中風運動功能恢復,斜方肌、中三角肌與後三角肌的C4-CMC在 FMA進步率越高,CMC變化率也越高,表示同側腦區也參與了調控,推測可能大腦調控在主要核心肌肉作用還不夠足以應付動作任務,因此活化其他肌肉收縮以提升力量來達成動作。
    ;The present study aims to evaluate the functional recovery of stroke patients in response to rehabilitation by Using Cortico-muscular coherence (CMC). Specifally, we correlated three existing arm movement functional scales on rehabilitation (FMA, TEMPA and WMFT) and CMC changes after intervention to determinate the efficacy difference between the conventional and virtual reality (VR) based rehabilitation.

    We recruited 17 subjects (male: 12; female: 5), the average age of 59.59 ± 12.10 years, seven of them accepted conventional rehabilitation, ten people accepted the virtual reality rehabilitation. All patients underwent a total 24 hours training program with the frequency of 1 hour a day, five days a week, and eight weeks per week. 30 channel EEG and 6 channel EMG were acquired before and after the rehabilitation training when patients did the shoulder flexion-extension using their affected hand. The CMC was computed at three different frequency bands (α: 8 ~ 15 Hz; β: 15 ~ 30 Hz; γ: 30 ~ 48 Hz). Clinical measures included FMA, TEMPA, WMFT were also conducted by the therapist pre- and post-treatment. We used regression analysis to evaluate the functional recovery with CMC and scores of clinical measures.The rmANOVA results of the outcome measurement indicated a significant effect on the intervention (p<0.001), measurement (p<0.001) and their interaction (p=0.024). We did not find a significant relation between EEG power over α and β band and FMA. However, the CMC analysis reveals that there are significant linear relation between C3 and several core muscles for moving the shoulder, including thetrapezius, anterior deltoid, middle deltoid, after deltoid and biceps in beta and gamma band. Furthermore, these CMCs are positively correlated with the functional improvement (i.e. the changes in FMA after rehabilitation). The CMC of C4 shows the similar patterns. We concluded that the increase of CMC after rehabilitation reflects the regain of control over muscles from the brain after damage.
    Appears in Collections:[生物醫學工程研究所 ] 博碩士論文

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