| DC 欄位 |
值 |
語言 |
| DC.contributor | 生醫科學與工程學系 | zh_TW |
| DC.creator | 趙珮筑 | zh_TW |
| DC.creator | PEI-ZHU ZHAO | en_US |
| dc.date.accessioned | 2024-7-26T07:39:07Z | |
| dc.date.available | 2024-7-26T07:39:07Z | |
| dc.date.issued | 2024 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=111852009 | |
| dc.contributor.department | 生醫科學與工程學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 運動帶給身體好處的同時也可能帶來傷害，物理性疲勞是其中一個誘發傷害產生的原因，其受傷機制包括神經肌肉控制、本體感覺、姿勢控制和運動協調性的改變，這些改變會影響動作模式，因此，如果可以在運動過程中即時發現有害的異常表現將有助於傷害的預防。
本實驗利用慣性測量單元(Inertial measurement unit, IMU）設計一種穿戴式裝置，在下肢多個關節放上感測點，記錄受試者動作中同步訊號，受試者為19歲到44歲的健康成年人，利用強度不同的有氧運動誘發疲勞，最後，將運動前後收集的訊號進行分析，找出最佳測量點與異常動作模式。
根據實驗，當達到疲勞強度時，跳躍高度與頻譜在疲勞前後均有顯著差異。對於IMU感測點放置的選擇，對於跳躍高度變化的測量，腳踝(p = 0.001)和股骨(p = 0.001)是相對較佳的選擇；對於頻譜變化的測量，膝蓋 (p = 0.047)是相對較佳的選擇。
希望透過穿戴式裝置收集同步訊號，分析潛在疲勞特徵，對疲勞進行管理與偵測，讓訓練員和運動者對會導致受傷的異常動作模式有更高的感知能力，有助於未來運動計畫的調整並防止過度訓練造成的損傷。 | zh_TW |
| dc.description.abstract | While exercise is beneficial to the body, it can also cause injuries. One reason for these injuries is physical fatigue, which affects mechanisms such as neuromuscular control, proprioception, posture control, and movement coordination. These changes can alter movement patterns. Therefore, detecting abnormal performance during exercise in real-time can help prevent injuries.
In this experiment, we designed a wearable device using inertial measurement units (IMUs). Sensors were placed on multiple joints of the lower limbs to record the synchronized signals. Participants were healthy adults aged 19 to 44. Fatigue was induced through aerobic exercises of varying intensity, and the signals were analyzed to identify the optimal measurement points and abnormal movement patterns.
According to the experiment, when participants reached fatigue intensity, there was a significant difference in jump height and frequency spectrum before and after fatigue. Regarding the choice of sensing point placement, for the measurement of jump height changes, ankle(p = 0.001) and femur(p = 0.001) are relatively better choices. For the measurement of spectrum changes, knee(p = 0.047) is relatively better choices.
We hope to use wearable devices to collect synchronized signals and analyze potential fatigue characteristics, so that we can manage and detect fatigue. Furthermore, Trainers and athletes will enhance the awareness of abnormal movement patterns that may lead to injuries. Finally, The ultimate goal is to prevent overtraining injuries by adjusting exercise program. | en_US |
| DC.subject | 慣性測量單元 | zh_TW |
| DC.subject | 疲勞 | zh_TW |
| DC.subject | 動作模式 | zh_TW |
| DC.subject | 同步訊號 | zh_TW |
| DC.subject | Inertial measurement unit | en_US |
| DC.subject | Fatigue | en_US |
| DC.subject | Movement patterns | en_US |
| DC.subject | Synchronized Signals | en_US |
| DC.title | 結合多關節慣性測量單元同步訊號比較運動疲勞前後 對下肢動作模式之影響 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Using Multi-joint Synchronized Signals from Inertial Measurement Unit to Compare the Effects of Fatigue on Lower Limb Movement Patterns Before and After Exercise | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |