The efficacy of a lifting strap as an ergonomic intervention for EMS providers: Does it make it easier to raise a supine patient to an upright sitting posture?

2021 ◽  
Vol 94 ◽  
pp. 103416
Author(s):  
Yilun Xu ◽  
Steven A. Lavender ◽  
Carolyn M. Sommerich
Author(s):  
Dr. Unnikrishnan VS ◽  
Dr. Prashanth AS

Now a days due to sedentary lifestyle and lack of time, people cannot concentrate on their proper regimen and people undergo many unwanted practices like faulty dietary habits, improper sitting posture, continuous work in one posture and overexertion, load bearing movements during travelling and sports. All these factors lead to the increase in the incidents of Manyasthambha in a large population. In classics Manyasthambha is explained under Vataja Nanatmaja Vikaras and is mentioned as Kaphaavruta Vata in its Samprapthi. While explaining treatment of Manyasthambha, Acharya Susruta clearly explains about Rooksha Sweda and Nasya which helps in the Samprapti Vighatana of Avarana in Manyasthambha.


2021 ◽  
Vol 17 (7) ◽  
pp. 155014772110248
Author(s):  
Miaoyu Li ◽  
Zhuohan Jiang ◽  
Yutong Liu ◽  
Shuheng Chen ◽  
Marcin Wozniak ◽  
...  

Physical health diseases caused by wrong sitting postures are becoming increasingly serious and widespread, especially for sedentary students and workers. Existing video-based approaches and sensor-based approaches can achieve high accuracy, while they have limitations like breaching privacy and relying on specific sensor devices. In this work, we propose Sitsen, a non-contact wireless-based sitting posture recognition system, just using radio frequency signals alone, which neither compromises the privacy nor requires using various specific sensors. We demonstrate that Sitsen can successfully recognize five habitual sitting postures with just one lightweight and low-cost radio frequency identification tag. The intuition is that different postures induce different phase variations. Due to the received phase readings are corrupted by the environmental noise and hardware imperfection, we employ series of signal processing schemes to obtain clean phase readings. Using the sliding window approach to extract effective features of the measured phase sequences and employing an appropriate machine learning algorithm, Sitsen can achieve robust and high performance. Extensive experiments are conducted in an office with 10 volunteers. The result shows that our system can recognize different sitting postures with an average accuracy of 97.02%.


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3588
Author(s):  
Yuki Iwata ◽  
Han Trong Thanh ◽  
Guanghao Sun ◽  
Koichiro Ishibashi

Heart rate measurement using a continuous wave Doppler radar sensor (CW-DRS) has been applied to cases where non-contact detection is required, such as the monitoring of vital signs in home healthcare. However, as a CW-DRS measures the speed of movement of the chest surface, which comprises cardiac and respiratory signals by body motion, extracting cardiac information from the superimposed signal is difficult. Therefore, it is challenging to extract cardiac information from superimposed signals. Herein, we propose a novel method based on a matched filter to solve this problem. The method comprises two processes: adaptive generation of a template via singular value decomposition of a trajectory matrix formed from the measurement signals, and reconstruction by convolution of the generated template and measurement signals. The method is validated using a dataset obtained in two different experiments, i.e., experiments involving supine and seated subject postures. Absolute errors in heart rate and standard deviation of heartbeat interval with references were calculated as 1.93±1.76bpm and 57.0±28.1s for the lying posture, and 9.72±7.86bpm and 81.3±24.3s for the sitting posture.


Author(s):  
Nusrat Binta Nizam ◽  
Tohfatul Jinan ◽  
Wahida Binte Naz Aurthy ◽  
Md. Rakib Hossen ◽  
Jahid Ferdous

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
F. Huppert ◽  
W. Betz ◽  
C. Maurer-Grubinger ◽  
F. Holzgreve ◽  
L. Fraeulin ◽  
...  

Abstract Background Musculoskeletal disorders (MSD) are a common health problem among dentists. Dental treatment is mainly performed in a sitting position. The aim of the study was to quantify the effect of different ergonomic chairs on the sitting position. In addition, it was tested if the sitting position of experienced workers is different from a non-dental group. Methods A total of 59 (28 m/31f) subjects, divided into two dentist groups according to their work experience (students and dentists (9 m/11f) < 10 years, dentists (9 m/10f) ≥ 10 years) and a control group (10 m/10f) were measured. A three-dimensional back scanner captured the bare back of all subjects sitting on six dentist’s chairs of different design. Initially, inter-group comparisons per chair, firstly in the habitual and secondly in the working postures, were carried out. Furthermore, inter-chair comparison was conducted for the habitual as well as for the working postures of all subjects and for each group. Finally, a comparison between the habitual sitting posture and the working posture for each respective chair (intra-chair comparison) was conducted (for all subjects and for each group). In addition, a subjective assessment of each chair was made. For the statistical analysis, non-parametric tests were conducted and the level of significance was set at 5%. Results When comparing the three subject groups, all chairs caused a more pronounced spinal kyphosis in experienced dentists. In both conditions (habitual and working postures), a symmetrical sitting position was assumed on each chair. The inter-chair comparisons showed no differences regarding the ergonomic design of the chairs. The significances found in the inter-chair comparisons were all within the measurementerror and could, therefore, be classified as clinically irrelevant. The intra-chair comparison (habitual sitting position vs. working sitting position) illustrated position-related changes in the sagittal, but not in the transverse, plane. These changes were only position-related (forward leaned working posture) and were not influenced by the ergonomic sitting design of the respective chair. There are no differences between the groups in the subjective assessment of each chair. Conclusions Regardless of the group or the dental experience, the ergonomic design of the dentist’s chair had only a marginal influence on the upper body posture in both the habitual and working sitting postures. Consequently, the focus of the dentist’s chair, in order to minimize MSD, should concentrate on adopting a symmetrical sitting posture rather than on its ergonomic design.


1960 ◽  
Vol 49 (2) ◽  
pp. 289-293 ◽  
Author(s):  
Frank Pierce Jones ◽  
Philip F. M. Gilley
Keyword(s):  

Author(s):  
Howraa Nash ◽  
Gourav Kumar Nayak ◽  
Jashwant Thota ◽  
Mohammed Alsowaidi ◽  
Hashem Alsowaidi ◽  
...  

A user’s posture at a computer workstation, especially wrist posture, is determined by the keyboard angle. Most commercially available computer keyboards have a built-in positive slope that requires the user to extend their wrist approximately 20° when typing. The purpose of this study is to find the negative keyboard angles that minimize wrist extension for both sitting and standing workstations. In this study, we compared upper limb working postures, including those of the wrist, elbow and shoulder, at 5 different keyboard angles between −16° and +6° in sitting and standing postures. Based on our results, we can conclude that the optimal range of keyboard slope is from −4° to −12° in sitting posture and −8° to −12° in the standing posture in terms of minimum wrist extension, typing performance, and user preference. We also propose a universal keyboard support design as an attachment to currently available keyboards.


2013 ◽  
Vol 54 (5) ◽  
pp. 1137 ◽  
Author(s):  
Byung-Hyun Park ◽  
Jeong-Hwan Seo ◽  
Myoung-Hwan Ko ◽  
Sung-Hee Park
Keyword(s):  

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