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Pubmed for Handhelds

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  • Title: Novel Foot Progression Angle Algorithm Estimation via Foot-Worn, Magneto-Inertial Sensing.
    Author: Huang Y, Jirattigalachote W, Cutkosky MR, Zhu X, Shull PB.
    Journal: IEEE Trans Biomed Eng; 2016 Nov; 63(11):2278-2285. PubMed ID: 26849858.
    Abstract:
    OBJECTIVE: The foot progression angle (FPA) is an important clinical measurement but currently can only be computed while walking in a laboratory with a marker-based motion capture system. This paper proposes a novel FPA estimation algorithm based on a single integrated sensor unit, consisting of an accelerometer, gyroscope, and magnetometer, worn on the foot. METHODS: The algorithm introduces a real-time heading vector with a complementary filter and utilizes a gradient descent method and zero-velocity update correction. Validation testing was performed by comparing FPA estimation from the wearable sensor with the standard FPAs computed from a marker-based motion capture system. Subjects performed nine walking trials of 2.5 min each on a treadmill. During each trial, subjects walked at one speed out of three options (1.0, 1.2, and 1.4 m/s) and walked with one gait pattern out of three options (normal, toe-in, and toe-out). RESULTS: The algorithm estimated FPA to within 0.2 ° of error or less for each walking conditions. CONCLUSION: A novel FPA algorithm has been introduced and described based on a single foot-worn sensor unit, and validation testing showed that FPA estimation was accurate for different walking speeds and foot angles. SIGNIFICANCE: This study enables future wearable systems gait research to assess or train walking patterns outside a laboratory setting in natural walking environments.
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