Real-world gait detection with a head-worn inertial unit and features-based machine learning

IF 2.4 3区 医学 Q3 NEUROSCIENCES Gait & posture Pub Date : 2024-10-01 Epub Date: 2024-10-30 DOI:10.1016/j.gaitpost.2024.08.068
P. Tasca , F. Salis , A. Cereatti
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利用头戴式惯性单元和基于特征的机器学习进行真实世界步态检测
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来源期刊
Gait & posture
Gait & posture 医学-神经科学
CiteScore
4.70
自引率
12.50%
发文量
616
审稿时长
6 months
期刊介绍: Gait & Posture is a vehicle for the publication of up-to-date basic and clinical research on all aspects of locomotion and balance. The topics covered include: Techniques for the measurement of gait and posture, and the standardization of results presentation; Studies of normal and pathological gait; Treatment of gait and postural abnormalities; Biomechanical and theoretical approaches to gait and posture; Mathematical models of joint and muscle mechanics; Neurological and musculoskeletal function in gait and posture; The evolution of upright posture and bipedal locomotion; Adaptations of carrying loads, walking on uneven surfaces, climbing stairs etc; spinal biomechanics only if they are directly related to gait and/or posture and are of general interest to our readers; The effect of aging and development on gait and posture; Psychological and cultural aspects of gait; Patient education.
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