scholarly journals Smart Chair for Monitoring of Sitting Behavior

2017 ◽  
Vol 2 (2) ◽  
pp. 274 ◽  
Author(s):  
Mengjie Huang ◽  
Ian Gibson ◽  
Rui Yang
Keyword(s):  
Human Body ◽  
Human Subjects ◽  
Healthcare Services ◽  
Human Computer Interactions ◽  
Intelligent Environment ◽  
Sitting Posture ◽  
Behavior Monitoring ◽  
Artificial Neural Network Classifier ◽  
Class 1 ◽  
Posture Monitoring

<p class="1">Sitting is a common behavior of human body in daily life. It is found that poor sitting postures can link to pains and other complications for people in literature. In order to avoid the adverse effects of poor sitting behavior, we have developed a highly practical design of smart chair system in this paper, which is able to monitor the sitting behavior of human body accurately and non-invasively. The pressure patterns of eight standardized sitting postures of human subjects were acquired and transmitted to the computer for the automatic sitting posture recognition with the application of artificial neural network classifier. The experimental results showed that it can recognize eight sitting postures of human subjects with high accuracy. The sitting posture monitoring in the developed smart chair system can help or promote people to achieve and maintain healthy sitting behavior, and prevent or reduce the chronic disease caused by poor sitting behavior. These promising results suggested that the presented system is feasible for sitting behavior monitoring, which can find applications in many areas including healthcare services, human-computer interactions and intelligent environment.</p>

scholarly journals Android Based Low Cost Sitting Posture Monitoring System

2020 ◽  
Author(s):  
Nusrat Binta Nizam ◽  
Tohfatul Jinan ◽  
Wahida Binte Naz Aurthy ◽  
Md. Rakib Hossen ◽  
Jahid Ferdous
Keyword(s):  
Monitoring System ◽  
Low Cost ◽  
Sitting Posture ◽  
Posture Monitoring

Tissue necrosis and passage of fluid due to cold stress from the thermally damaged human body peripherals: A mathematical model

2015 ◽  
Vol 04 (02) ◽  
pp. 1550012
Author(s):  
M. A. Khanday ◽  
Fida Hussain ◽  
Khalid Nazir
Keyword(s):  
Mathematical Model ◽  
Finite Element ◽  
Heat Equation ◽  
Cold Stress ◽  
Human Body ◽  
Human Subjects ◽  
Diffusion Equations ◽  
Tissue Necrosis ◽  
Cold Temperatures ◽  
Element Technique

The development of cold injury takes place in the human subjects by means of crystallization of tissues in the exposed regions at severe cold temperatures. The process together with the evaluation of the passage of fluid discharge from the necrotic regions with respect to various degrees of frostbites has been carried out by using variational finite element technique. The model is based on the Pennes' bio-heat equation and mass diffusion equations together with suitable initial and boundary conditions. The results are analyzed in relation with atmospheric temperatures and other parameters of the tissue medium.

A Sensing Chair

1999 ◽  
Author(s):  
Hong Z. Tan
Keyword(s):  
Automatic Control ◽  
Real Time ◽  
Classification System ◽  
Tracking System ◽  
Pressure Sensors ◽  
Sensory Systems ◽  
Human Computer Interactions ◽  
Sitting Posture ◽  
Haptic Sensing ◽  
Posture Tracking

Abstract This paper is concerned with how objects in an environment can be made aware of people via haptic sensing. It was motivated by the desire to make our environment “smarter” by providing it with sensory systems similar to our own. The work reported here focuses on an object that is involved in virtually all human-computer interactions, yet has remained sensory-deprived — the chair. A real-time sitting posture classification system has been developed using surface-mounted pressure sensors placed on the seatpan and backrest of a chair. The ultimate goal of this work is to build a robust multi-user sitting-posture tracking system that will have many applications including ergonomics and automatic control of airbag deployment in a car. Challenges for reaching the goal and plans of nature work are discussed.

Ultrasound Imaging Characterization of Soft Tissue Dynamics of the Seated Human Body

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Daisuke Yamada ◽  
Alperen Değirmenci ◽  
Robert D. Howe
Keyword(s):  
Ultrasound Imaging ◽  
Human Body ◽  
Human Subjects ◽  
Excitation Amplitude ◽  
Whole Body ◽  
Ultrasound Images ◽  
Body Dynamics ◽  
Excitation Pattern

Abstract To characterize the dynamics of internal soft organs and external anatomical structures, this paper presents a system that combines medical ultrasound imaging with an optical tracker and a vertical exciter that imparts whole-body vibrations on seated subjects. The spatial and temporal accuracy of the system was validated using a phantom with calibrated internal structures, resulting in 0.224 mm maximum root-mean-square (r.m.s.) position error and 13 ms maximum synchronization error between sensors. In addition to the dynamics of the head and sternum, stomach dynamics were characterized by extracting the centroid of the stomach from the ultrasound images. The system was used to characterize the subject-specific body dynamics as well as the intrasubject variabilities caused by excitation pattern (frequency up-sweep, down-sweep, and white noise, 1–10 Hz), excitation amplitude (1 and 2 m/s2 r.m.s.), seat compliance (rigid and soft), and stomach filling (empty and 500 mL water). Human subjects experiments (n = 3) yielded preliminary results for the frequency response of the head, sternum, and stomach. The method presented here provides the first detailed in vivo characterization of internal and external human body dynamics. Tissue dynamics characterized by the system can inform design of vehicle structures and adaptive control of seat and suspension systems, as well as validate finite element models for predicting passenger comfort in the early stages of vehicle design.

The Key Role of Headrest Optimization in Driver Comfort

2019 ◽  
Vol 24 (3) ◽  
pp. 592-599
Author(s):  
Hamid Gheibollahi ◽  
Masoud Masih-Tehrani ◽  
Mohammadmehdi Niroobakhsh
Keyword(s):  
Human Body ◽  
The Body ◽  
Human Body Model ◽  
Sitting Posture ◽  
Conventional Vehicle ◽  
Body Model ◽  
Basic Model ◽  
Proposed Model ◽  
Stiffness And Damping

In this study, adding a headrest to the conventional vehicle driver seat is investigated to improve the driver comfort and decrease the driver damages. For this purpose, a conventional biomechanical human body model of wholebody vibrations is provided and modified by adding a head degree of freedom to the body model and a headrest to the seat model. The basic model is in the sitting posture, lumped parameters and has nine DOFs for the human body, on contrary to the proposed model which has ten DOFs. The new human body DOF is the twisting motion of the head and neck. This new DOF is generated because of headrest adding to the driver’s seat. To determine the head discomforts, the Seat to Head (STH) indexes are studied in two directions: horizontal and vertical. The Genetic Algorithm (GA) is used to optimize the STH in different directions. The optimization variables are stiffness and damping parameters of the driver’s seat which are 12 for the basic model and are 16 for a new seat. The integer programming is used for time reduction. The results show that new seat (equipped by headrest) has very better STH in both directions.

Self-Assisted Care System for Human Mobility

2004 ◽  
Vol 16 (5) ◽  
pp. 464-472
Author(s):  
Teruhisa Onishi ◽  
◽  
Tatsuo Arai ◽  
Kenji Inoue ◽  
Yasushi Mae ◽  
...  
Keyword(s):  
Human Body ◽  
Human Mobility ◽  
The Body ◽  
Wearable Device ◽  
End Effector ◽  
Sitting Posture ◽  
Holding Device ◽  
Physically Challenged ◽  
Care System

Since humans are bipedal, it is easy to become bedridden when the hip and legs become weakened or disabled due to aging or other causes. If such physically challenged people are enabled to get up from bed and move to a nearby location, however, they could use their arms and hands to do certain tasks such as taking meals or writing. In this paper, we propose a wearable device for supporting the human body that can be easily worn or removed by means of a body-holding device. The hoisting device has an arm which, as an end-effector, supports the body and allows the user to rise from bed and lie down again. In addition, a three-point fixing mechanism is used to maintain the user’s sitting posture at a desk, and to realize an integrated self-assisted care system.

Deafness

2020 ◽  
pp. 212-222
Author(s):  
Rebecca Sanchez
Keyword(s):  
Human Body ◽  
Human Subjects ◽  
Spring Water ◽  
Signed Languages ◽  
Signed Language

This chapter describes deaf experiences of reading, particularly those that occur in signed languages. It explores both visual and tactile methods of signed language reading and analyzes the ways these practices enable alternative theorizations of reading and its potentials as well as the reasons that referring to the processes of decoding signed language utterances as reading is appropriate. Specifically, it focuses on the implications of encountering the human body as text and the relationships between human subjects and language that become possible in such contexts through readings of several ASSL poems including Bernard Bragg’s “Flowers and Moonlight on Spring Water” and “The Pilot and the Eagle,” Ian Sanborn’s “Caterpillar,” and Ayisha Knight-Shaw’s “Until.”

Dynamic ease evaluation for 3D garment design

2018 ◽  
Vol 22 (2) ◽  
pp. 209-222
Author(s):  
Fangfang Zhang ◽  
Trevor John Little
Keyword(s):  
Human Body ◽  
Design Methodology ◽  
Human Subjects ◽  
Essential Element ◽  
The Body ◽  
Upper Arm ◽  
Core Element ◽  
Content Type ◽  
Comfort Evaluation ◽  
Garment Design

Purpose 3D garment design technology is developing rapidly thereby creating a need for different approaches to developing the patterns. The purpose of this paper is to evaluate the 3D dynamic ease distribution for a 3D garment design. Design/methodology/approach Standard garments were created from Size 2 to Size 14 for ten human subjects. Landmarks location on both human body and the standard garment under dynamic postures are recorded, and he fit and comfort evaluation of the standard garment were collected from the ten human subjects. Finally, these data were used to evaluate the 3D dynamic ease distribution for a 3D garment design. Findings 3D dynamic ease evaluation is challenging and the findings showed that the upper-arm design is a core element of the whole 3D garment design. The upper arm is not only a connecting part for both front and back pieces of the garment, but is also the main active part of the body, so it is the essential element to affect the comfort and fit of the garment under dynamic postures. Originality/value This research provides a novel 3D ease evaluation by analyzing the landmarks location of both human body and standard garment, and fit and comfort evaluation of the standard garment, which are all carried under dynamic postures.

scholarly journals AI-powered Posture Training: Application of Machine Learning in Sitting Posture Recognition Using the LifeChair Smart Cushion

2019 ◽  
Author(s):  
Katia Bourahmoune ◽  
Toshiyuki Amagasa
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Well Being ◽  
Recognition System ◽  
Training System ◽  
Sensor Data ◽  
Physical And Mental Health ◽  
Sitting Posture ◽  
Posture Monitoring ◽  
Posture Recognition

Humans spend on average more than half of their day sitting down. The ill-effects of poor sitting posture and prolonged sitting on physical and mental health have been extensively studied, and solutions for curbing this sedentary epidemic have received special attention in recent years. With the recent advances in sensing technologies and Artificial Intelligence (AI), sitting posture monitoring and correction is one of the key problems to address for enhancing human well-being using AI. We present the application of a sitting posture training smart cushion called LifeChair that combines a novel pressure sensing technology, a smartphone app interface and machine learning (ML) for real-time sitting posture recognition and seated stretching guidance. We present our experimental design for sitting posture and stretch pose data collection using our posture training system. We achieved an accuracy of 98.93% in detecting more than 13 different sitting postures using a fast and robust supervised learning algorithm. We also establish the importance of taking into account the divergence in user body mass index in posture monitoring. Additionally, we present the first ML-based human stretch pose recognition system for pressure sensor data and show its performance in classifying six common chair-bound stretches.

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