Sleep monitoring system based on body posture movement using Microsoft Kinect sensor

2019 ◽  
Author(s):  
Nityacas Febriana ◽  
Achmad Rizal ◽  
Erwin Susanto
Keyword(s):  
Monitoring System ◽  
Body Posture ◽  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Sleep Monitoring ◽  
Microsoft Kinect Sensor

scholarly journals Sleep Monitoring System Using Kinect Sensor

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jaehoon Lee ◽  
Min Hong ◽  
Sungyong Ryu
Keyword(s):  
Sleep Quality ◽  
Monitoring System ◽  
Human Body ◽  
Human Life ◽  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Sleep Monitoring ◽  
Related Data ◽  
Related Information

Sleep activity is one of crucial factors for determining the quality of human life. However, a traditional sleep monitoring system onerously requires many devices to be attached to human body for achieving sleep related information. In this paper, we proposed and implemented the sleep monitoring system which can detect the sleep movement and posture during sleep using a Microsoft Kinect v2 sensor without any body attached devices. The proposed sleep monitoring system can readily gather the sleep related information that can reveal the sleep patterns of individuals. We expect that the analyzed sleep related data can significantly improve the sleep quality.

scholarly journals Can shoulder range of movement be measured accurately using the Microsoft Kinect sensor plus Medical Interactive Recovery Assistant (MIRA) software?

2017 ◽  
Vol 26 (12) ◽  
pp. e382-e389 ◽  
Author(s):  
James D. Wilson ◽  
Jennifer Khan-Perez ◽  
Dominic Marley ◽  
Susan Buttress ◽  
Michael Walton ◽  
...  
Keyword(s):  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Range Of Movement ◽  
Shoulder Range ◽  
Microsoft Kinect Sensor

Microsoft Kinect Sensor and Its Effect

2012 ◽  
Vol 19 (2) ◽  
pp. 4-10 ◽  
Author(s):  
Zhengyou Zhang
Keyword(s):  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Microsoft Kinect Sensor

A multimodal LIBRAS-UFOP Brazilian sign language dataset of minimal pairs using a microsoft Kinect sensor

2020 ◽  
pp. 114179
Author(s):  
Lourdes Ramirez Cerna ◽  
Edwin Escobedo Cardenas ◽  
Dayse Garcia Miranda ◽  
David Menotti ◽  
Guillermo Camara-Chavez
Keyword(s):  
Sign Language ◽  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Minimal Pairs ◽  
Brazilian Sign Language ◽  
Microsoft Kinect Sensor

scholarly journals Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study

Sensors ◽  
2017 ◽  
Vol 17 (2) ◽  
pp. 286 ◽  
Author(s):  
Ali Al-Naji ◽  
Kim Gibson ◽  
Sang-Heon Lee ◽  
Javaan Chahl
Keyword(s):  
Pilot Study ◽  
Real Time ◽  
Microsoft Kinect ◽  
Kinect Sensor ◽  
Microsoft Kinect Sensor

Motion Performance Measurement using the Microsoft Kinect Sensor

2013 ◽  
Vol 2 (4) ◽  
pp. 28-37 ◽  
Author(s):  
Maliheh Fakhar ◽  
Saeed Behzadipour ◽  
Amir Mobini
Keyword(s):  
Performance Measurement ◽  
Healthy Subject ◽  
Microsoft Kinect ◽  
Upper Body ◽  
Kinect Sensor ◽  
Performance Indices ◽  
Kinematic Data ◽  
Home Based ◽  
Motion Performance ◽  
Microsoft Kinect Sensor

In this study, motion performance indices based on the kinematics of upper body have been presented and compared to be used in a home-based rehabilitation device. Microsoft Kinect sensor is used to extract and calculate such indices. A set of experiments has been designed and carried out in which, kinematic data of three patients has been recorded. Finally, the selected indices have been calculated, and the results were compared with those of a healthy subject.

scholarly journals Skeleton based gait recognition for long and baggy clothes

2019 ◽  
Vol 277 ◽  
pp. 03005
Author(s):  
Abrar Alharbi ◽  
Fahad Alharbi ◽  
Eiji Kamioka
Keyword(s):  
Gait Recognition ◽  
User Interaction ◽  
Microsoft Kinect ◽  
Human Gait ◽  
Kinect Sensor ◽  
Recognition Method ◽  
Walking Gait ◽  
Biometric Feature ◽  
Gait Database ◽  
Microsoft Kinect Sensor

Human gait is a significant biometric feature used for the identification of people by their style of walking. Gait offers recognition from a distance at low resolution while requiring no user interaction. On the other hand, other biometrics are likely to require a certain level of interaction. In this paper, a human gait recognition method is presented to identify people who are wearing long baggy clothes like Thobe and Abaya. Microsoft Kinect sensor is used as a tool to establish a skeleton based gait database. The skeleton joint positions are obtained and used to create five different datasets. Each dataset contained different combination of joints to explore their effectiveness. An evaluation experiment was carried out with 20 walking subjects, each having 25 walking sequences in total. The results achieved good recognition rates up to 97%.

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