دورية أكاديمية

A human lower-limb biomechanics and wearable sensors dataset during cyclic and non-cyclic activities

التفاصيل البيبلوغرافية
العنوان: A human lower-limb biomechanics and wearable sensors dataset during cyclic and non-cyclic activities
المؤلفون: Keaton Scherpereel, Dean Molinaro, Omer Inan, Max Shepherd, Aaron Young
المصدر: Scientific Data, Vol 10, Iss 1, Pp 1-12 (2023)
بيانات النشر: Nature Portfolio, 2023.
سنة النشر: 2023
المجموعة: LCC:Science
مصطلحات موضوعية: Science
الوصف: Abstract Tasks of daily living are often sporadic, highly variable, and asymmetric. Analyzing these real-world non-cyclic activities is integral for expanding the applicability of exoskeletons, protheses, wearable sensing, and activity classification to real life, and could provide new insights into human biomechanics. Yet, currently available biomechanics datasets focus on either highly consistent, continuous, and symmetric activities, such as walking and running, or only a single specific non-cyclic task. To capture a more holistic picture of lower limb movements in everyday life, we collected data from 12 participants performing 20 non-cyclic activities (e.g. sit-to-stand, jumping, squatting, lunging, cutting) as well as 11 cyclic activities (e.g. walking, running) while kinematics (motion capture and IMUs), kinetics (force plates), and electromyography (EMG) were collected. This dataset provides normative biomechanics for a highly diverse range of activities and common tasks from a consistent set of participants and sensors.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2052-4463
Relation: https://doaj.org/toc/2052-4463
DOI: 10.1038/s41597-023-02840-6
URL الوصول: https://doaj.org/article/2b565334ab4341388ef55f7877cc7737
رقم الأكسشن: edsdoj.2b565334ab4341388ef55f7877cc7737
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20524463
DOI:10.1038/s41597-023-02840-6