ArticleSensors (Basel, Switzerland)2016
An Integrated Wireless Wearable Sensor System for Posture Recognition and Indoor Localization.
Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Microwave Devices for Wearable Sensors and IoT.Sensors (Basel, Switzerland) · 2023Review
- Fall Detection System-Based Posture-Recognition for Indoor Environments.Journal of imaging · 2021Article
- Personalized Human Activity Recognition Based on Integrated Wearable Sensor and Transfer Learning.Sensors (Basel, Switzerland) · 2021Article
- A Pedestrian Dead Reckoning Method for Head-Mounted Sensors.Sensors (Basel, Switzerland) · 2020Article
- Reinforcement Learning Based Fast Self-Recalibrating Decoder for Intracortical Brain-Machine Interface.Sensors (Basel, Switzerland) · 2020Article
- A Posture Recognition Method Based on Indoor Positioning Technology.Sensors (Basel, Switzerland) · 2019Article
- UWB Monitoring System for AAL Applications.Sensors (Basel, Switzerland) · 2017Article
- Upper Limb Rehabilitation Robot Powered by PAMs Cooperates with FES Arrays to Realize Reach-to-Grasp Trainings.Journal of healthcare engineering · 2017Article
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Authors and funding
4 authors.
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Abstract
In order to provide better monitoring for the elderly or patients, we developed an integrated wireless wearable sensor system that can realize posture recognition and indoor localization in real time. Five designed sensor nodes which are respectively fixed on lower limbs and a standard Kalman filter are used to acquire basic attitude data. After the attitude angles of five body segments (two thighs, two shanks and the waist) are obtained, the pitch angles of the left thigh and waist are used to realize posture recognition. Based on all these attitude angles of body segments, we can also calculate the coordinates of six lower limb joints (two hip joints, two knee joints and two ankle joints). Then, a novel relative localization algorithm based on step length is proposed to realize the indoor localization of the user. Several sparsely distributed active Radio Frequency Identification (RFID) tags are used to correct the accumulative error in the relative localization algorithm and a set-membership filter is applied to realize the data fusion. The experimental results verify the effectiveness of the proposed algorithms.
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