Classification of Fall Directions via Wearable Motion Sensors

2021 ◽  
pp. 103129
Author(s):  
Mustafa Şahin Turan ◽  
Billur Barshan
2015 ◽  
Vol 110 ◽  
pp. 91-102 ◽  
Author(s):  
L.A. González ◽  
G.J. Bishop-Hurley ◽  
R.N. Handcock ◽  
C. Crossman

2008 ◽  
Vol 28 (1) ◽  
pp. 120-126 ◽  
Author(s):  
A. Findlow ◽  
J.Y. Goulermas ◽  
C. Nester ◽  
D. Howard ◽  
L.P.J. Kenney

2017 ◽  
Vol 5 (42) ◽  
pp. 11092-11099 ◽  
Author(s):  
Qi Li ◽  
Jin Li ◽  
Danhquang Tran ◽  
Chengqiang Luo ◽  
Yang Gao ◽  
...  

Strain sensors based on a porous CNT/PDMS nanocomposite can detect a collection of human body motions and actuation of soft robotics.


ASAIO Journal ◽  
2018 ◽  
Vol 64 (3) ◽  
pp. 351-359 ◽  
Author(s):  
Jacob A. Garlant ◽  
Kaitlyn R. Ammann ◽  
Marvin J. Slepian

2012 ◽  
Vol 3 (3) ◽  
pp. 45-53
Author(s):  
Stéphane Bonnet ◽  
Pierre Jallon ◽  
Alain Bourgerette ◽  
Michel Antonakios ◽  
Vencesslass Rat ◽  
...  

In several biomedical domains, it would be interesting to monitor subjects over night time using wearable motion sensors and trigger an alarm if a specific movement has been detected by processing the accelerometer readings. In this paper, the authors describe an innovative architecture for such an alarm system in the context of epilepsy monitoring. The main ingredients of the proposed system are wireless motion sensors, a radio-frequency transceiver linked to an Ethernet gateway and an acquisition server that incorporates real-time detection method. This motion analysis system is further integrated in the dataflow of an existing medicalized alarm system and an event is sent to healthcare professionals every time a seizure is detected by the expert system. The EPIMOUV system has been evaluated, during a 6-month period, in a specialized institution with epilepsy pharmaco-resistant residents.


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