Fall prediction based on biomechanics equilibrium using Kinect
The fall is one of the most important research fields of solitary elder healthcare at home based on Internet of Things technology. Current studies mainly focus on the fall detection, which helps medical staffs bring a fallen elder out of danger in time. However, it neither predicts a fall nor provid...
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| Format: | Article |
| Language: | English |
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Wiley
2017-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717703257 |
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| _version_ | 1849399699530842112 |
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| author | Xu Tao Zhou Yun |
| author_facet | Xu Tao Zhou Yun |
| author_sort | Xu Tao |
| collection | DOAJ |
| description | The fall is one of the most important research fields of solitary elder healthcare at home based on Internet of Things technology. Current studies mainly focus on the fall detection, which helps medical staffs bring a fallen elder out of danger in time. However, it neither predicts a fall nor provides an effective protection against a fall. This article studies the fall prediction based on human biomechanics equilibrium and body posture characteristics through analyzing three-dimensional skeleton joints data from the depth camera sensor Kinect. The research includes building a human bionic mass model using skeleton joints data from Kinect, determining human balance state, and proposing a fall prediction algorithm based on recurrent neural networks by unbalanced posture features. We evaluate the model and algorithm on an open database. The performance indicates that the fall prediction algorithm by studying human biomechanics can predict a fall (91.7%) and provide a certain amount of time (333 ms) before the elder injuring (hitting the floor). This work provides a technical basis and a data analytics approach for the fall protection. |
| format | Article |
| id | doaj-art-9c629fc2d86d437ba707662a7958ff17 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-9c629fc2d86d437ba707662a7958ff172025-08-20T03:38:16ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-04-011310.1177/1550147717703257Fall prediction based on biomechanics equilibrium using KinectXu Tao0Zhou Yun1State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, P.R. ChinaSchool of Education, Shaanxi Normal University, Xi’an, P.R. ChinaThe fall is one of the most important research fields of solitary elder healthcare at home based on Internet of Things technology. Current studies mainly focus on the fall detection, which helps medical staffs bring a fallen elder out of danger in time. However, it neither predicts a fall nor provides an effective protection against a fall. This article studies the fall prediction based on human biomechanics equilibrium and body posture characteristics through analyzing three-dimensional skeleton joints data from the depth camera sensor Kinect. The research includes building a human bionic mass model using skeleton joints data from Kinect, determining human balance state, and proposing a fall prediction algorithm based on recurrent neural networks by unbalanced posture features. We evaluate the model and algorithm on an open database. The performance indicates that the fall prediction algorithm by studying human biomechanics can predict a fall (91.7%) and provide a certain amount of time (333 ms) before the elder injuring (hitting the floor). This work provides a technical basis and a data analytics approach for the fall protection.https://doi.org/10.1177/1550147717703257 |
| spellingShingle | Xu Tao Zhou Yun Fall prediction based on biomechanics equilibrium using Kinect International Journal of Distributed Sensor Networks |
| title | Fall prediction based on biomechanics equilibrium using Kinect |
| title_full | Fall prediction based on biomechanics equilibrium using Kinect |
| title_fullStr | Fall prediction based on biomechanics equilibrium using Kinect |
| title_full_unstemmed | Fall prediction based on biomechanics equilibrium using Kinect |
| title_short | Fall prediction based on biomechanics equilibrium using Kinect |
| title_sort | fall prediction based on biomechanics equilibrium using kinect |
| url | https://doi.org/10.1177/1550147717703257 |
| work_keys_str_mv | AT xutao fallpredictionbasedonbiomechanicsequilibriumusingkinect AT zhouyun fallpredictionbasedonbiomechanicsequilibriumusingkinect |