Wearable technology for posture monitoring at the workplace

Bootsman, Rik; Markopoulos, Panos; Qi, Qi; Wang, Qi; Timmermans, Annick

doi:10.1016/j.ijhcs.2019.08.003

Cited by 66 publications

(103 citation statements)

References 29 publications

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“…Moreover, they argued that while such exercises do not require exertion, doing them regularly could be a challenge for computer workers. We thus decided to go beyond using sensors to track posture and to provide notification alerts for poor posture as is done with some commercial systems (e.g., Alex [ 25 ]) or other experimental posture-tracking applications (e.g., [ 29 , 30 ]). Such posture tracking could be helpful, but suffers from an important limitation: people’s neck posture is most likely to be static for a long time exactly when they need to work long hours and are under time pressure, in which case they are also likely to ignore posture related notifications.…”

Section: The Design Of Neckiomentioning

confidence: 99%

Neckio: Motivating Neck Exercises in Computer Workers

Markopoulos

Shen

Wang

et al. 2020

Sensors

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Neck pain is common among computer workers who may spend too much time in a static posture facing their display. Regular breaks and variety in one’s posture can help to prevent discomfort and pain. In order to understand how to support computer workers to do so regularly, we surveyed a convenience sample of computer workers (N = 130) regarding their work habits and their attitudes towards neck exercises at the workplace. The survey showed that they are highly motivated, but not able to comply with a neck exercise program. To address this challenge, we designed Neckio, a system that is aimed at encouraging posture variation and facilitating neck exercises at work. Neckio consists in an interactive application and a wireless angulation sensing appliance that can be mounted on the headset that office workers often use for reasons of privacy. Next to providing an interactive exercise program suitable for the workplace, its design places emphasis on an engaging user experience. We report a short-term user experience valuation of Neckio in an actual office environment (N = 10). Participants rated the overall user experience positively and reported to be intrinsically motivated to do the neck exercises. These results indicate the potential of the Neckio as a behavior change support technology to reduce the risk of developing neck pain in computer workers.

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Section: The Design Of Neckiomentioning

confidence: 99%

Neckio: Motivating Neck Exercises in Computer Workers

Markopoulos

Shen

Wang

et al. 2020

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Additionally, office people now sit for long periods of time everyday 7 . Maintaining such one single posture for a long time might probably lead to disorders in the spine 8 , as well as fatigue for their body, regarded as the major factors resulting in a significant increase in the risk of back pain 9 , 10 . According to recent researches, over 60% of Americans and 50% of Europeans are about to experience back and neck pain at some point in their lives 11 , 12 .…”

Section: Introductionmentioning

confidence: 99%

Sensing of joint and spinal bending or stretching via a retractable and wearable badge reel

Liu

et al. 2021

Nat Commun

148

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Human motions, such as joint/spinal bending or stretching, often contain information that is useful for orthopedic/neural disease diagnosis, rehabilitation, and prevention. Here, we show a badge-reel-like stretch sensing device with a grating-structured triboelectric nanogenerator exhibiting a stretching sensitivity of 8 V mm−1, a minimum resolution of 0.6 mm, a low hysteresis, and a high durability (over 120 thousand cycles). Experimental and theoretical investigations are performed to define the key features of the device. Studies from human natural daily activities and exercise demonstrate the functionality of the sensor for real-time recording of knee/arm bending, neck/waist twisting, and so on. We also used the device in a spinal laboratory, monitoring human subjects’ spine motions, and validated the measurements using the commercial inclinometer and hunchback instrument. We anticipate that the lightweight, precise and durable stretch sensor applied to spinal monitoring could help mitigate the risk of long-term abnormal postural habits induced diseases.

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“…Advanced technologies in treatment and nursing field [ 3 – 6 ] include the Internet of Things (IoT) technologies [ 2 ], biosensor technologies, big data [ 7 ], and cloud computing [ 8 – 12 ]. With advanced information technologies, the medical efficiency and healthy living standard of the public can be improved significantly [ 13 , 14 ]. Smart geriatric nursing is a must since China has become an aging society.…”

Section: Introductionmentioning

confidence: 99%

A Simple Framework of Smart Geriatric Nursing considering Health Big Data and User Profile

Tang

2020

Computational and Mathematical Methods in Medicine

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The National Bureau of Statistics of China shows that the population over 65 years old in China exceeds 166 million accounting for 11.93% of the total population by the end of 2018. The importance and severity of taking care of the elderly are becoming increasingly prominent. High-quality and meticulous care for the daily life of the elderly needs helpful and advanced sciences and technologies. Smart geriatric nursing is a must. Basing on the professional knowledge of geriatric nursing, this paper proposes a framework of smart geriatric nursing which consists of three aspects of smart nursing: smart geriatric nursing in physical health using biosensor and advanced devices, smart geriatric nursing in mental health based on user profile, and smart geriatric nursing for daily life based on big data in health. The deployment of the proposed method relies on the technologies of the Internet of Things (IoT), user profile system, big data, and many other advanced information technologies. The framework of methods can provide a useful reference for the systematic technical scheme of smart geriatric nursing in an aging society.

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Wearable technology for posture monitoring at the workplace

Cited by 66 publications

References 29 publications

Neckio: Motivating Neck Exercises in Computer Workers

Neckio: Motivating Neck Exercises in Computer Workers

Sensing of joint and spinal bending or stretching via a retractable and wearable badge reel

A Simple Framework of Smart Geriatric Nursing considering Health Big Data and User Profile

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