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The study on walking intention detection of knee joint anterior d | 28125
Orthopedic & Muscular System: Current Research

Orthopedic & Muscular System: Current Research
Open Access

ISSN: 2161-0533

+44-20-4587-4809

The study on walking intention detection of knee joint anterior displacement using rollator based on IR sensor


International Conference and Expo on Biomechanics & Implant Design

July 27-29, 2015 Orlando, USA

Seongmi Song, Hyunjong Lee, Seungrok Kang, Giltae Yang, Changho Yu and Taekyu Kwon

Posters-Accepted Abstracts: Orthop Muscular Syst

Abstract :

To compensate the defect of rollator based on FSR (Force Sensing Resistor) or force sensor such as velocity control problem ongait slopes, Knee joint anterior displacement was investigated to detect walking intention detection using IR (Infraed Ray) sensors. Leg muscle activities and foot pressure are also measured in order to verify our investigation. Two IR sensors are placed on the center of rollator to sense right and left legsâ�?�? walking intention. EMG signal was monitored rectus femoirs, biceps femoris, tibialis anterior, and gastrocnemius. Pedar-X system measured foot pressure (forefoot, mid foot, hindfoot, and average pressure). Twenty healthy males (age 24.3�?±1.5 years, height 174.7�?±5.3, and weight 72.6�?±4.6kg) were involved in experiments which had been preceded 30 minutes a week, during 3 weeks. The gait slope and increasing velocity situation show that knee joint anterior displacement was increased. Based on EMG and foot pressure results, femoral region musclesâ�?�? activation increased and load activated was concentrated on hindfoot in volar titling case. On the contrary, lower leg muscles were more activated and concentrated load was located in forefoot. These results were similar to knee joint anterior displacement from IR sensors.

Biography :

Seongmi Song has completed her bachelor?s degree from Chonbuk National University in Biomedical Engineering and she is working towards a master?s degree from Chonbuk National University in Healthcare Engineering. She is interested in fall detection based on gait analysis and nanomaterials.

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