• The Journal of Korean Physical Therapy
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• v.23 no.3
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• pp.49-56
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• 2011

Purpose: To evaluate changes in lower extremity muscle activity caused by high heeled shoe wearing during normal, brisk, and upslope walking. Methods: Twenty healthy young women (age, $23.9{\pm}2.47$) participated in this study. Muscle activities of the tibialis anterior, peroneus longus, gastrocnemius lateralis, gastrocnemius medialis, soleus, hamstring, vastus lateralis, and vastus medialis while walking normally, walking briskly, and walking up a slope. Results: When walking normally, the peroneus longus, gastrocnemius lateralis, soleus, and vastus lateralis evidenced higher activity when high-heeled shoes were worn (p<0.05). During brisk walking, the peroneus longus and gastrocnemius lateralis exhibited higher activity (p<0.05). Although the peroneus longus and vastus lateralis exhibited higher activity when walking up an incline with high-heeled shoes, the activity levels of the tibialis anterior and gastrocnemius medialis were lower (p<0.05). Conclusion: The results of this study demonstrate that increased heel height substantially reduces muscle effort when walking up a slope. From a therapeutic perspective, it is possible that using high heeled shoes over a short period might enhance muscle activity of ankle evertor, although it can cause mediolateral muscle imbalances in the lower extremities.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.81-89
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• 2017

In this paper, we propose a gait pattern recognition method for intelligent prosthesis that enables walking in various environments of femoral amputees. The proposed gait mode changing method is a single sensor based algorithm which can discriminate gait surface and gait phase using only strain gauges sensor, and it is designed to simplify the algorithm based on multiple sensors of existing intelligent prosthesis and to reduce cost of prosthesis system. For the recognition algorithm, we analyzed characteristics of the ground reaction force generated during gait of normal person and defined gait step segmentation and gait detection condition, A gait analyzer was constructed for the gait experiment in the environment similar to the femoral amputee. The validity of the paper was verified through the defined detection conditions and fabricated instruments. The accuracy of the algorithm based on the single sensor was 95%. Based on the proposed single sensor-based algorithm, it is considered that the intelligent prosthesis system can be made inexpensive, and the user can directly grasp the state of the walking surface and shift the walking mode. It is confirmed that it is possible to change the automatic walking mode to switch the walking mode that is suitable for the walking mode.