Smart-Cover: A real time sitting posture monitoring system

Anwary, Arif Reza; Çetinkaya, Deniz; Vassallo, Michael; Bouchachia, Hamid

doi:10.1016/j.sna.2020.112451

Cited by 29 publications

(10 citation statements)

References 36 publications

(36 reference statements)

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“…Anwary et al [ 40 ] proposed an asymmetric posture detection system based on custom-made pressure sensors made from Velostat, a piezoelectric conductive material coupled to polyethylene foam and placed between two layers of conductive fabric. Four sensors embedded in the seat and two in the backrest provide the data to measure mild, moderate, and severe asymmetry of the sitting position based on a fuzzy logic algorithm.…”

Section: Related Workmentioning

confidence: 99%

IoT System for Real-Time Posture Asymmetry Detection

Mura

Gregorio

Lamberti

et al. 2023

Sensors

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The rise of the Internet of Things (IoT) has enabled the development of measurement systems dedicated to preventing health issues and monitoring conditions in smart homes and workplaces. IoT systems can support monitoring people doing computer-based work and avoid the insurgence of common musculoskeletal disorders related to the persistence of incorrect sitting postures during work hours. This work proposes a low-cost IoT measurement system for monitoring the sitting posture symmetry and generating a visual alert to warn the worker when an asymmetric position is detected. The system employs four force sensing resistors (FSR) embedded in a cushion and a microcontroller-based read-out circuit for monitoring the pressure exerted on the chair seat. Java-based software performs the real-time monitoring of the sensors’ measurements and implements an uncertainty-driven asymmetry detection algorithm. The shifts from a symmetric to an asymmetric posture and vice versa generate and close a pop-up warning message, respectively. In this way, the user is promptly notified when an asymmetric posture is detected and invited to adjust the sitting position. Every position shift is recorded in a web database for further analysis of the sitting behavior.

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Section: Related Workmentioning

confidence: 99%

IoT System for Real-Time Posture Asymmetry Detection

Mura

Gregorio

Lamberti

et al. 2023

Sensors

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“…Experimental results show that 59%, 82%, and 92% accuracy are obtained using the pressure sensors, the distance sensors, and the fusion of pressure and distance sensors, respectively. Anwary et al developed a chair seat cover embedded with pressure sensors, which used rule-based classifiers to detect extended periods of sitting in an asymmetrical posture [9]. Bourahmoune et al proposed a machine learning-based sitting posture and stretch recognition system with a pressure-sensing IoT cushion [10].…”

Section: Introductionmentioning

confidence: 99%

iGuard: an intelligent sitting posture monitoring system with pressure sensors

Yan,

Wang

2023

Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023)

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Prolonged and poor sitting postures are major causes of many musculoskeletal disorders, such as herniated discs, cervical spondylosis, back fasciitis, and scoliosis, and hence proper postures are essential for maintaining good health. Towards a pervasive and low-cost healthcare system, we in this study design and implement a sitting posture monitoring system, named iGuard, with a pressure sensor array. Specifically, we use five sensors to sense the sitting posture information and naturally annotate the training sensor readings over a while. Afterward, we segment the streaming data and extract a variety of time-domain and frequency-domain features from the segments to train a sitting posture recognition model. Finally, comparative experiments are conducted to evaluate the performance of iGuard in distinguishing normal, left-leaning, right-leaning, forward-leaning, backward-leaning, left-leg crossed, and right-leg crossed sitting postures. Particularly, we consider three different evaluation schemes, i.e., subject-dependent setting, subject-independent setting, and cross-subject setting. Experimental results demonstrate the effectiveness of iGuard.

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“…Asymmetric sitting biomechanics has been overviewed with the help of a seat cover that employed novel pressure sensing architecture as an endpoint application. Using this device to monitor sitting posture can help correct posture and prevent health problems while transforming the usually expensive and time-consuming method into a 30 min IoT-based procedure [ 36 ]. IoT-type devices that comprise thin sensors are the next step in point of care testing (POCT) and personalised medicine [ 37 ] for tailored diagnostics and therapy that addresses each patient’s needs based on their specific background, disease prognosis, and assessed risks [ 38 ].…”

Section: Introductionmentioning

confidence: 99%

Early Notice Pointer, an IoT-like Platform for Point-of-Care Feet and Body Balance Screening

et al. 2022

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Improper foot biomechanics associated with uneven bodyweight distribution contribute to impaired balance and fall risks. There is a need to complete the panel of commercially available devices for the self-measurement of BMI, fat, muscle, bone, weight, and hydration with one that measures weight-shifting at home as a pre-specialist assessment system. This paper reports the development of the Early Notice Pointer (ENP), a user-friendly screening device based on weighing scale technology. The ENP is designed to be used at home to provide a graphic indication and customised and evidence-based foot and posture triage. The device electronically detects and maps the bodyweight and distinct load distributions on the main areas of the feet: forefoot and rearfoot. The developed platform also presents features that assess the user’s balance, and the results are displayed as a simple numerical report and map. The technology supports data display on mobile phones and accommodates multiple measurements for monitoring. Therefore, the evaluation could be done at non-specialist and professional levels. The system has been tested to validate its accuracy, precision, and consistency. A parallel study to describe the frequency of arch types and metatarsal pressure in young adults (1034 healthy subjects) was conducted to explain the importance of self-monitoring at home for better prevention of foot arch- and posture-related conditions. The results showed the potential of the newly created platform as a screening device ready to be wirelessly connected with mobile phones and the internet for remote and personalised identification and monitoring of foot- and body balance-related conditions. The real-time interpretation of the reported physiological parameters opens new avenues toward IoT-like on-body monitoring of human physiological signals through easy-to-use devices on flexible substrates for specific versatility.

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Smart-Cover: A real time sitting posture monitoring system

Cited by 29 publications

References 36 publications

IoT System for Real-Time Posture Asymmetry Detection

IoT System for Real-Time Posture Asymmetry Detection

iGuard: an intelligent sitting posture monitoring system with pressure sensors

Early Notice Pointer, an IoT-like Platform for Point-of-Care Feet and Body Balance Screening

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