Automatic semantic labelling of human motion activity

2006 ◽  
Author(s):  
A. Garg ◽  
A. Naftel
Keyword(s):  
Human Motion ◽  
Motion Activity ◽  
Semantic Labelling

Low Power ASIC for Monitoring Human Motion Activity

2015 ◽  
Vol 135 (5) ◽  
pp. 178-183
Author(s):  
Fumihiro Washino ◽  
Yuki Matsumoto ◽  
Tomoya Tanaka ◽  
Koji Sonoda ◽  
Kensuke Kanda ◽  
...  
Keyword(s):  
Low Power ◽  
Human Motion ◽  
Motion Activity

scholarly journals A durable nanomesh on-skin strain gauge for natural skin motion monitoring with minimum mechanical constraints

2020 ◽  
Vol 6 (33) ◽  
pp. eabb7043 ◽  
Author(s):  
Yan Wang ◽  
Sunghoon Lee ◽  
Tomoyuki Yokota ◽  
Haoyang Wang ◽  
Zhi Jiang ◽  
...  
Keyword(s):  
Strain Gauge ◽  
Body Movement ◽  
Full Range ◽  
Human Motion ◽  
Activity Monitoring ◽  
Continuous Motion ◽  
Widespread Application ◽  
Mechanical Constraints ◽  
Human Motion Detection ◽  
Motion Activity

Ultraconformable strain gauge can be applied directly to human skin for continuous motion activity monitoring, which has seen widespread application in interactive robotics, human motion detection, personal health monitoring, and therapeutics. However, the development of an on-skin strain gauge that can detect human body motions over a long period of time without disturbing the natural skin movements remains a challenge. Here, we present an ultrathin and durable nanomesh strain gauge for continuous motion activity monitoring that minimizes mechanical constraints on natural skin motions. The device is made from reinforced polyurethane-polydimethylsiloxane (PU-PDMS) nanomeshes and exhibits excellent sustainability, linearity, and durability with low hysteresis. Its thinness geometry and softness provide minimum mechanical interference on natural skin deformations. During speech, the nanomesh-attached face exhibits skin strain mapping comparable to that of a face without nanomeshes. We demonstrate long-term facial stain mapping during speech and the capability for real-time stable full-range body movement detection.

scholarly journals Fusion of Multiple Lidars and Inertial Sensors for the Real-Time Pose Tracking of Human Motion

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5342
Author(s):  
Ashok Kumar Patil ◽  
Adithya Balasubramanyam ◽  
Jae Yeong Ryu ◽  
Pavan Kumar B N ◽  
Bharatesh Chakravarthi ◽  
...  
Keyword(s):  
Real Time ◽  
Inertial Sensors ◽  
Tracking System ◽  
Initial Step ◽  
Human Motion ◽  
Position Estimation ◽  
Measurement Unit ◽  
Multiple Sensors ◽  
Pose Tracking ◽  
Motion Activity

Today, enhancement in sensing technology enables the use of multiple sensors to track human motion/activity precisely. Tracking human motion has various applications, such as fitness training, healthcare, rehabilitation, human-computer interaction, virtual reality, and activity recognition. Therefore, the fusion of multiple sensors creates new opportunities to develop and improve an existing system. This paper proposes a pose-tracking system by fusing multiple three-dimensional (3D) light detection and ranging (lidar) and inertial measurement unit (IMU) sensors. The initial step estimates the human skeletal parameters proportional to the target user’s height by extracting the point cloud from lidars. Next, IMUs are used to capture the orientation of each skeleton segment and estimate the respective joint positions. In the final stage, the displacement drift in the position is corrected by fusing the data from both sensors in real time. The installation setup is relatively effortless, flexible for sensor locations, and delivers results comparable to the state-of-the-art pose-tracking system. We evaluated the proposed system regarding its accuracy in the user’s height estimation, full-body joint position estimation, and reconstruction of the 3D avatar. We used a publicly available dataset for the experimental evaluation wherever possible. The results reveal that the accuracy of height and the position estimation is well within an acceptable range of ±3–5 cm. The reconstruction of the motion based on the publicly available dataset and our data is precise and realistic.

Editorial: Human motion perception, eye movements, and orientation in visual space

2000 ◽  
Vol 59 (2) ◽  
pp. 85-88 ◽  
Author(s):  
Rudolf Groner ◽  
Marina T. Groner ◽  
Kazuo Koga
Keyword(s):  
Eye Movements ◽  
Motion Perception ◽  
Visual Space ◽  
Human Motion

Sound impacts on motion activity of upper limb fingers

2003 ◽  
Vol 9 (1s) ◽  
pp. 36-39
Author(s):  
E.A. Ilchenko ◽  
Keyword(s):  
Upper Limb ◽  
Motion Activity

Saving and Reproduction of Human Motion Data by Using Haptic Devices with Different Configurations

2011 ◽  
Vol 131 (3) ◽  
pp. 267-274 ◽  
Author(s):  
Noboru Tsunashima ◽  
Yuki Yokokura ◽  
Seiichiro Katsura
Keyword(s):  
Human Motion ◽  
Haptic Devices ◽  
Motion Data

Integrated Reproduction of Human Motion Components by Motion Copying System

2010 ◽  
Vol 130 (4) ◽  
pp. 436-442 ◽  
Author(s):  
Noboru Tsunashima ◽  
Seiichiro Katsura
Keyword(s):  
Human Motion

Computational Studies of Human Motion: Part 1, Tracking and Motion Synthesis

2005 ◽  
Author(s):  
David A. Forsyth ◽  
Okan Arikan ◽  
Leslie Ikemoto ◽  
James O'Brien ◽  
Deva Ramanan
Keyword(s):  
Human Motion ◽  
Computational Studies ◽  
Motion Synthesis
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