Upper arm

2022 ◽  
pp. 25-39
Author(s):  
Chong Tae Kim
Keyword(s):  
2019 ◽  
Vol 25 ◽  
pp. 173
Author(s):  
Magnus Löndahl ◽  
Mona Landin-Olsson ◽  
Stig Attval ◽  
Colleen Mdingi ◽  
Katherine S Tweden
Keyword(s):  

1982 ◽  
Vol 9 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Ruyao Song ◽  
Yeguang Song ◽  
Yuseng Yu ◽  
Yeliang Song
Keyword(s):  

2020 ◽  
Vol 82 (3) ◽  
pp. 179-182
Author(s):  
Maiko YOSHIDA ◽  
Ayaka ETO ◽  
Takeshi NAKAHARA ◽  
Masutaka FURUE

2016 ◽  
Vol 78 (6) ◽  
pp. 600-602
Author(s):  
Sayuri SATO ◽  
Shin-ichi ANSAI ◽  
Toshiharu YAMASHITA

2020 ◽  
Author(s):  
Anis Davoudi ◽  
Mamoun T. Mardini ◽  
Dave Nelson ◽  
Fahd Albinali ◽  
Sanjay Ranka ◽  
...  

BACKGROUND Research shows the feasibility of human activity recognition using Wearable accelerometer devices. Different studies have used varying number and placement for data collection using the sensors. OBJECTIVE To compare accuracy performance between multiple and variable placement of accelerometer devices in categorizing the type of physical activity and corresponding energy expenditure in older adults. METHODS Participants (n=93, 72.2±7.1 yrs) completed a total of 32 activities of daily life in a laboratory setting. Activities were classified as sedentary vs. non-sedentary, locomotion vs. non-locomotion, and lifestyle vs. non-lifestyle activities (e.g. leisure walk vs. computer work). A portable metabolic unit was worn during each activity to measure metabolic equivalents (METs). Accelerometers were placed on five different body positions: wrist, hip, ankle, upper arm, and thigh. Accelerometer data from each body position and combinations of positions were used in developing Random Forest models to assess activity category recognition accuracy and MET estimation. RESULTS Model performance for both MET estimation and activity category recognition strengthened with additional accelerometer devices. However, a single accelerometer on the ankle, upper arm, hip, thigh, or wrist had only a 0.03 to 0.09 MET increase in prediction error as compared to wearing all five devices. Balanced accuracy showed similar trends with slight decreases in balanced accuracy for detection of locomotion (0-0.01 METs), sedentary (0.13-0.05 METs) and lifestyle activities (0.08-0.04 METs) compared to all five placements. The accuracy of recognizing activity categories increased with additional placements (0.15-0.29). Notably, the hip was the best single body position for MET estimation and activity category recognition. CONCLUSIONS Additional accelerometer devices only slightly enhance activity recognition accuracy and MET estimation in older adults. However, given the extra burden of wearing additional devices, single accelerometers with appropriate placement appear to be sufficient for estimating energy expenditure and activity category recognition in older adults.


PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e91335 ◽  
Author(s):  
Masatoshi Shiono ◽  
Shin Takahashi ◽  
Yuichi Kakudo ◽  
Masanobu Takahashi ◽  
Hideki Shimodaira ◽  
...  

2015 ◽  
Vol 04 (01) ◽  
pp. 043-045
Author(s):  
Gyata Mehta ◽  
Varsha Mokhasi

AbstractThe median nerve is formed in the axilla by fusion of the two roots from the lateral and medial cords. The present case report describes an anomalous presentation of double formation of median nerve and its relation with axillary and brachial arteries. The median nerve was formed in two stages at different levels, first in the axilla and then in the upper arm by receiving double contribution from the lateral root of the lateral cord, which fuse with the medial root of the medial cord to form the median nerve. The formation took place medial to the axillary artery in the axilla and antero-medial to the brachial artery in the arm. Such anatomical variations and their relation with the arteries are important for the surgeons and anesthesiologists and of great academic interest to the anatomists.


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