작업 관련 근골격계 질환의 위험성 저감을 위한 작업 자세 및 동작의 인간공학 연구

학위논문(박사) -- 서울대학교대학원 : 공과대학 산업공학과, 2022.2. 박우진.육체적 부하가 큰 자세 및 동작으로 작업을 수행하는 것은 작업자의 근골격계 질환의 위험성을 증가시킨다. 작업자의 근골격계에 가해지는 육체적 부하의 양상은 수행하는 작업의 종류에 따라 달라진다. 장시간 앉은 자세로 작업을 수행하는 경우, 작업자의 근육, 인대와 같은 연조직에 과도한 부하가 발생하여 목, 허리 등 다양한 신체 부위에서 근골격계 질환의 위험성이 증가할 수 있다. 따라서, 착좌 시 발생할 수 있는 근골격계 질환의 위험성을 저감하기 위해서는 작업자의 착좌 자세를 실시간으로 모니터링하고, 이에 대한 피드백을 제공하는 것이 필요하다. 들기 작업과 같은 동적인 움직임이 포함된 작업을 수행하는 경우, 작업자의 체중이 신체적 부하에 영향을 미칠 수 있다. 전세계적인 비만의 유행으로 인해 많은 작업자들이 체중 증가를 겪고 있고, 들기 작업과 같은 동적인 작업에서 비만은 신체적 부하에 악영향을 미칠 수 있다. 따라서, 비만과 작업 관련 근골격계 질환의 위험성은 잠재적인 연관성을 가지고 있고, 비만이 들기 작업에 미치는 생체역학적 영향을 논의할 필요성이 있다. 작업장에서의 근골격계 질환의 위험성을 저감하기 위해 다양한 연구들이 수행되어 왔지만, 작업 시스템의 인간공학적 설계 측면에서 추가적인 연구가 필요하다. 장시간 의자에 앉아 정적인 작업을 수행하는 작업자의 근골격계 질환을 저감하기 위한 유망한 방법 중 하나로, 작업자의 자세를 실시간으로 모니터링하고 분류하는 시스템을 개발하는 것이 제안되고 있다. 이러한 시스템은 작업자가 근골격계 질환의 위험성이 낮은 자세를 작업 시간 동안 유지하도록 돕는 데 활용될 수 있을 것이다. 기존의 대부분의 자세 모니터링 시스템에서는 분류할 자세를 정의하는 과정에서 인간공학적 문헌이 거의 고려되지 않았고, 사용자가 실제로 활용하기에는 여러 한계점들이 존재하였다. 들기 작업의 경우, 체질량 지수(BMI) 40 이상의 초고도 비만 작업자의 동작 패턴을 논의한 연구는 거의 찾아볼 수 없었다. 또한, 다양한 들기 작업 조건 하에서 전신 관절들의 움직임을 생체역학적 측면에서 분석한 연구는 부족한 실정이다. 따라서, 본 연구에서의 연구 목적은 1) 다양한 센서 조합을 활용한 실시간 착좌 자세를 분류하는 시스템을 개발하고, 2) 들기 작업 시 초고도 비만이 개별 관절의 움직임과 들기 동작 패턴에 미치는 영향을 이해하여, 다양한 종류의 작업에서 발생할 수 있는 근골격계 질환의 위험성을 저감하는 것이다. 연구 목적을 달성하기 위해 다음의 두 가지 연구를 수행하였다. 첫번째 연구에서는 실시간으로 착좌 자세를 분류하는 스마트 의자 시스템을 개발하였다. 스마트 의자 시스템은 각각 여섯 개의 거리 센서와 압력 센서를 조합하여 구성되었다. 착좌 관련한 근골격계 질환에 대해 문헌 조사를 수행하였고, 이를 바탕으로 결정된 자세들에 대해 서른 여섯 명의 데이터를 수집하였다. 스마트 의자 시스템에서 자세를 분류하기 위해 kNN 알고리즘을 활용하였고, 성능을 검증하기 위해 단일 종류의 센서로 구성된 기준 모델들과 비교를 수행하였다. 분류 성능을 비교한 결과, 센서를 조합한 스마트 의자 시스템이 가장 우수한 결과를 보였다. 두번째 연구에서는 들기 작업을 수행할 때 초고도 비만이 개별 관절의 움직임과 동작 패턴에 미치는 영향을 분석하기 위해 모션 캡쳐 실험을 수행하였다. 들기 실험에는 근골격계 질환 이력이 없는 서른 다섯 명이 참여하였다. 수집된 데이터를 바탕으로 주요 관절(발목, 무릎, 엉덩이, 허리, 어깨, 팔꿈치) 별 운동역학적 변수들과, 들기 동작의 패턴을 표현하는 동작 지수들을 계산하였다. 들기 작업 조건과 비만 수준에 따라, 대부분의 변수에서 통계적으로 유의한 차이를 보였다. 전체적으로 비만인은 정상체중인에 비해 다리 보다 허리를 사용하여 들기 작업을 수행하였고, 동작 수행 시 상대적으로 적은 관절 각도 변화와 느린 움직임을 보였다. 들기 작업에서 박스의 이동에 개별 관절이 기여하는 비율도 정상체중인과 비만인은 다른 패턴을 보였다. 본 연구의 결과를 활용하여 다양한 종류의 신체적 부하에 노출된 작업자들의 근골격계 질환의 위험성을 저감할 수 있고, 궁극적으로 업무의 생산성과 개인의 건강을 제고할 수 있을 것이다. 첫번째 연구에서 개발된 스마트 의자 시스템은 기존 자세 분류 시스템의 단점들을 완화하였다. 개발된 시스템은 저렴한 소수의 센서만을 활용하여 근골격계 측면에서 중요한 자세들을 높은 정확도로 분류하였다. 이러한 자세 분류 시스템은 작업자에게 실시간으로 자세 피드백을 제공하여, 근골격계 질환의 위험성이 낮은 자세를 유지하는 데 활용될 수 있을 것이다. 두번째 연구의 결과는 동적인 작업 시 초고도 비만으로 인한 잠재적인 근골격계 질환의 위험성을 이해하는 데 활용될 수 있다. 초고도 비만인과 정상체중인 간 관절의 움직임과 동작의 차이를 이해하여, 비만을 고려한 인간공학적 작업장 설계와 동작 가이드라인을 제공할 수 있을 것이다.Working in stressful postures and movements increases the risk of work-related musculoskeletal disorders (WMSDs). The physical stress on a worker’s musculoskeletal system depends on the type of work task. In the case of sedentary work, stressful sitting postures for prolonged durations could increase the load on soft connective tissues such as muscles and ligaments, resulting in the incidence of WMSDs. Therefore, to reduce the WMSDs, it is necessary to monitor a worker’s sitting posture and additionally provide ergonomic interventions. When the worker performs a task that involves dynamic movements, such as manual lifting, the worker’s own body mass affects the physical stress on the musculoskeletal system. In the global prevalence of obesity in the workforce, an increase in the body weight of the workers could adversely affect the musculoskeletal system during the manual lifting task. Therefore, obesity could be associated with the development of WMSDs, and the impacts of obesity on workers’ movement during manual lifting need to be examined. Despite previous research efforts to prevent WMSDs, there still exist research gaps concerning ergonomics design of work systems. For sedentary workers, a promising solution to reduce the occurrence of WMSDs is the development of a system capable of monitoring and classifying a seated worker's posture in real-time, which could be utilized to provide feedback to the worker to maintain a posture with a low-risk of WMSDs. However, the previous studies in relation to such a posture monitoring system lacked a review of the ergonomics literature to define posture categories for classification, and had some limitations in widespread use and user acceptance. In addition, only a few studies related to obesity impacts on manual lifting focused on severely obese population with a body mass index (BMI) of 40 or higher, and, analyzed lifting motions in terms of multi-joint movement organization or at the level of movement technique. Therefore, the purpose of this study was to: 1) develop a sensor-embedded posture classification system that is capable of classifying an instantaneous sitting posture as one of the posture categories discussed in the ergonomics literature while not suffering from the limitations of the previous system, and, 2) identify the impacts of severe obesity on joint kinematics and movement technique during manual lifting under various task conditions. To accomplish the research objectives, two major studies were conducted. In the study on the posture classification system, a novel smart chair system was developed to monitor and classify a worker’s sitting postures in real-time. The smart chair system was a mixed sensor system utilizing six pressure sensors and six infrared reflective distance sensors in combination. For a total of thirty-six participants, data collection was conducted on posture categories determined based on an analysis of the ergonomics literature on sitting postures and sitting-related musculoskeletal problems. The mixed sensor system utilized a kNN algorithm for posture classification, and, was evaluated in posture classification performance in comparison with two benchmark systems that utilized only a single type of sensors. The mixed sensor system yielded significantly superior classification performance than the two benchmark systems. In the study on the manual lifting task, optical motion capture was conducted to examine differences in joint kinematics and movement technique between severely obese and non-obese groups. A total of thirty-five subjects without a history of WMSDs participated in the experiment. The severely obese and non-obese groups show significant differences in most joint kinematics of the ankle, knee, hip, spine, shoulder, and elbow. There were also significant differences between the groups in the movement technique index, which represents a motion in terms of the relative contribution of an individual joint degree of freedom to the box trajectory in a manual lifting task. Overall, the severely obese group adopted the back lifting technique (stoop) rather than the leg lifting technique (squat), and showed less joint range of excursions and slow movements compared to the non-obese group. The findings mentioned above could be utilized to reduce the risk of WMSDs among workers performing various types of tasks, and, thus, improve work productivity and personal health. The mixed sensor system developed in this study was free from the limitations of the previous posture monitoring systems, and, is low-cost utilizing only a small number of sensors; yet, it accomplishes accurate classification of postures relevant to the ergonomic analyses of seated work tasks. The mixed sensor system could be utilized for various applications including the development of a real-time posture feedback system for preventing sitting-related musculoskeletal disorders. The findings provided in the manual lifting study would be useful in understanding the potential risk of WMSDs for severely obese workers. Differences in joint kinematics and movement techniques between severely obese and non-obese groups provide practical implications concerning the ergonomic design of work tasks and workspace layout.Chapter 1. Introduction 1 1.1 Research Background 1 1.2 Research Objectives 5 1.3 Dissertation Outline 6 Chapter 2. Literature Review 8 2.1 Work-related Musculoskeletal Disorders Among Sedentary Workers 8 2.1.1 Relationship Between Sitting Postures and Musculoskeletal Disorders 8 2.1.2 Systems for Monitoring and Classifying a Seated Worker's Postures 10 2.2 Impacts of Obesity on Manual Works 22 2.2.1 Impacts of Obesity on Work Capacity 22 2.2.2 Impacts of Obesity on Joint Kinematics and Biomechanical Demands 24 Chapter 3. Developing and Evaluating a Mixed Sensor Smart Chair System for Real-time Posture Classification: Combining Pressure and Distance Sensors 27 3.1 Introduction 27 3.2 Materials and Methods 33 3.2.1 Predefined posture categories for the mixed sensor system 33 3.2.2 Physical construction of the mixed sensor system 36 3.2.3 Posture Classifier Design for the Mixed Sensor System 38 3.2.4 Data Collection for Training and Testing the Posture Classifier of the Mixed Sensor System 41 3.2.5 Comparative Evaluation of Posture Classification Performance 43 3.3 Results 46 3.3.1 Model Parameters and Features 46 3.3.2 Posture Classification Performance 47 3.4 Discussion 50 Chapter 4. Severe Obesity Impacts on Joint Kinematics and Movement Technique During Manual Load Lifting 57 4.1 Introduction 57 4.2 Methods 61 4.2.1 Participants 61 4.2.2 Experimental Task 61 4.2.3 Experimental Procedure 64 4.2.4 Data Processing 65 4.2.5 Experimental Variables 67 4.2.6 Statistical Analysis 71 4.3 Results 72 4.3.1 Kinematic Variables 72 4.3.2 Movement Technique Indexes 83 4.4 Discussion 92 Chapter 5. Conclusion 102 5.1 Summary 102 5.2 Implications 105 5.3 Limitations and Future Directions 106 Bibliography 108 국문초록 133박

Wearable textile elongation sensor

This work shows a developed wearable elongation sensor based on an optical fiber. The presented approach to sew a fiber optic into a lycra textile enables the modulation of light amplitude in respect to textile strain. This apparatus in combination with small-size instrumentation enables the development of a wearable textile garment capable of monitoring and acquiring strain data, and send it wirelessly to a base station. The light amplitude increases with the increment of textile strain. The output voltage remains stable over time for the resting and maximum textile strain position

Detection of Spine curvature using wireless sensors

Ankylosing spondylitis (AS) is a progressive disease of the spine where the spine slowly stiffens and can eventually become completely inflexible. It can be difficult to diagnose in primary care, and thus there is often a 10-year delay in diagnosis. Within this study an intelligent wearable system is designed and developed to detect the displacement of the spine and provide the subject with a continuous posture monitoring and feedback signals when an incorrect posture is detected using accelerometer and gyroscope sensors. This wearable system can be used both to diagnose AS in early stages and to prevent subjects from lower back and neck pain caused by incorrect posture. We outline here the system which detects the curvature of the spine by using Shimmer sensors placed on the back and provides relevant exercises based on the user’s pain records

Preliminary Validity and Acceptability of Motion Tape for Measuring Low Back Movement: Mixed Methods Study.

BACKGROUND: Low back pain (LBP) is a significant public health problem that can result in physical disability and financial burden for the individual and society. Physical therapy is effective for managing LBP and includes evaluation of posture and movement, interventions directed at modifying posture and movement, and prescription of exercises. However, physical therapists have limited tools for objective evaluation of low back posture and movement and monitoring of exercises, and this evaluation is limited to the time frame of a clinical encounter. There is a need for a valid tool that can be used to evaluate low back posture and movement and monitor exercises outside the clinic. To address this need, a fabric-based, wearable sensor, Motion Tape (MT), was developed and adapted for a low back use case. MT is a low-profile, disposable, self-adhesive, skin-strain sensor developed by spray coating piezoresistive graphene nanocomposites directly onto commercial kinesiology tape. OBJECTIVE: The objectives of this study were to (1) validate MT for measuring low back posture and movement and (2) assess the acceptability of MT for users. METHODS: A total of 10 participants without LBP were tested. A 3D optical motion capture system was used as a reference standard to measure low back kinematics. Retroreflective markers and a matrix of MTs were placed on the low back to measure kinematics (motion capture) and strain (MT) simultaneously during low back movements in the sagittal, frontal, and axial planes. Cross-correlation coefficients were calculated to evaluate the concurrent validity of MT strain in reference motion capture kinematics during each movement. The acceptability of MT was assessed using semistructured interviews conducted with each participant after laboratory testing. Interview data were analyzed using rapid qualitative analysis to identify themes and subthemes of user acceptability. RESULTS: Visual inspection of concurrent MT strain and kinematics of the low back indicated that MT can distinguish between different movement directions. Cross-correlation coefficients between MT strain and motion capture kinematics ranged from -0.915 to 0.983, and the strength of the correlations varied across MT placements and low back movement directions. Regarding user acceptability, participants expressed enthusiasm toward MT and believed that it would be helpful for remote interventions for LBP but provided suggestions for improvement. CONCLUSIONS: MT was able to distinguish between different low back movements, and most MTs demonstrated moderate to high correlation with motion capture kinematics. This preliminary laboratory validation of MT provides a basis for future device improvements, which will also involve testing in a free-living environment. Overall, users found MT acceptable for use in physical therapy for managing LBP

Low Cost Plastic Optical Fiber Pressure Sensor Embedded in Mattress for Vital Signal Monitoring

[EN] The aim of this paper is to report the design of a low-cost plastic optical fiber (POF) pressure sensor, embedded in a mattress. We report the design of a multipoint sensor, a cheap alternative to the most common fiber sensors. The sensor is implemented using Arduino board, standard LEDs for optical communication in POF (¿ = 645 nm) and a silicon light sensor. The Super ESKA® plastic fibers were used to implement the fiber intensity sensor, arranged in a 4 × 4 matrix. During the breathing cycles, the force transmitted from the lungs to the thorax is in the order of tens of Newtons, and the respiration rate is of one breath every 2¿5 s (0.2¿0.5 Hz). The sensor has a resolution of force applied on a single point of 2.2¿4.5%/N on the normalized voltage output, and a bandwidth of 10 Hz, it is then suitable to monitor the respiration movements. Another issue to be addressed is the presence of hysteresis over load cycles. The sensor was loaded cyclically to estimate the drift of the system, and the hysteresis was found to be negligible.This research was supported by FINESSE project, funded by the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Action grant agreement No. 722509 and PROMETEO 2017/103 Tecnologias y Aplicaciones Futura de la Fotonica de Microondas.Sartiano, D.; Sales Maicas, S. (2017). Low Cost Plastic Optical Fiber Pressure Sensor Embedded in Mattress for Vital Signal Monitoring. Sensors. 17 (12)(2900):1-11. https://doi.org/10.3390/s17122900S11117 (12)290

Wearable technology for spine movement assessment: A systematic review

Continuous monitoring of spine movement function could enhance our understanding of low back pain development. Wearable technologies have gained popularity as promising alternative to laboratory systems in allowing ambulatory movement analysis. This paper aims to review the state of art of current use of wearable technology to assess spine kinematics and kinetics. Four electronic databases and reference lists of relevant articles were searched to find studies employing wearable technologies to assess the spine in adults performing dynamic movements. Two reviewers independently identified relevant papers. Customised data extraction and quality appraisal form were developed to extrapolate key details and identify risk of biases of each study. Twenty-two articles were retrieved that met the inclusion criteria: 12 were deemed of medium quality (score 33.4-66.7%), and 10 of high quality (score> 66.8%). The majority of articles (19/22) reported validation type studies. Only 6 reported data collection in real-life environments. Multiple sensors type were used: electrogoniometers (3/22), strain gauges based sensors (3/22), textile piezoresistive sensor (1/22) and accelerometers often used with gyroscopes and magnetometers (15/22). Two sensors units were mainly used and placing was commonly reported on the spine lumbar and sacral regions. The sensors were often wired to data transmitter/logger resulting in cumbersome systems. Outcomes were mostly reported relative to the lumbar segment and in the sagittal plane, including angles, range of motion, angular velocity, joint moments and forces. This review demonstrates the applicability of wearable technology to assess the spine, although this technique is still at an early stage of development

An investigation into the utility of wearable sensor derived biofeedback on the motor control of the lumbar spine

Lower back pain (LBP) is a disability that affects a large proportion of the population and treatment for this has been shifting towards a more individualized, patient-centered approach. There has been a recent uptake in the utilization and implementation of wearable sensors that can administer biofeedback in various industrial, clinical, and performance-based settings. The overall aim of this Master’s thesis was to investigate how wearable sensors can be used in a sensorimotor (re)training approach, including how sensory biofeedback from wearable sensors can be used to improve measures of spinal motor control and proprioception. Two complementary research studies were completed to address this overall aim. As a systematic review, Study #1 focused on addressing the lack of consensus surrounding wearable sensor derived biofeedback and spine motor control. The results of this review suggest that haptic/vibrotactile feedback is the most common and that it is administered in an instantaneous real-time manner within most experimental paradigms. Further, study #1 identified clear gaps within the research literature. Specifically, future research would benefit from more clarity regarding study design, and movement instructions, and explicit definitions of biofeedback parameters to enhance reproducibility. The aim of Study #2 was to assess the acute effects of wearable sensor-derived auditory biofeedback on gross lumbar proprioception. To assess this, participants completed a target repositioning protocol, followed by a training period where they were provided with auditory feedback for two of four targets based on a percentage of their lumbar ROM. Results suggest that mid-range targets benefitted most from the acute auditory feedback training. Further, individuals with poorer repositioning abilities in the pre-training assessment showed the greatest improvements from the auditory feedback training. This suggests that auditory biofeedback training may be an effective tool to improve proprioception in those with proprioceptive deficits. Collectively these complimentary research studies will improve the understanding surrounding the ecological utility of wearable sensor derived biofeedback in industrial, clinical, and performance settings to enhance to sensorimotor control of the lumbar region

Sensores de fibra ótica para arquiteturas e-Health

In this work, optical fiber sensors were developed and optimized for biomedical applications in wearable and non-intrusive and/or invisible solutions. As it was intended that the developed devices would not interfere with the user's movements and their daily life, the fibre optic sensors presented several advantages when compared to conventional electronic sensors, among others, the following stand out: size and reduced weight, biocompatibility, safety, immunity to electromagnetic interference and high sensitivity. In a first step, wearable devices with fibre optic sensors based in Fiber Bragg gratings (FBG) were developed to be incorporated into insoles to monitor different walking parameters based on the analysis of the pressure exerted on several areas of the insole. Still within this theme, other sensors were developed using the same sensing technology, but capable of monitoring pressure and shear forces simultaneously. This work was pioneering and allowed monitoring one of the main causes of foot ulceration in people with diabetes: shear. At a later stage, the study focused on the issue related with the appearance of ulcers in people with reduced mobility and wheelchair users. In order to contribute to the mitigation of this scourge, a system was developed composed of a network of fibre optic sensors capable of monitoring the pressure at various points of the wheelchair. It not only measures the pressure at each point, but also monitors the posture of the wheelchair user and advises him/her to change posture regularly to reduce the probability of this pathology occurring. Still within this application, another work was developed where the sensor not only monitored the pressure but also the temperature in each of the analysis points, thus indirectly measuring shear. In another phase, plastic fibre optic sensors were studied and developed to monitor the body posture of an office chair user. Simultaneously, software was developed capable of monitoring and showing the user all the acquired data in real time and warning for incorrect postures, as well as advising for work breaks. In a fourth phase, the study focused on the development of highly sensitive sensors embedded in materials printed by a 3D printer. The sensor was composed of an optical fibre with a FBG and the sensor body of a flexible polymeric material called "Flexible". This material was printed on a 3D printer and during its printing the optical fibre was incorporated. The sensor proved to be highly sensitive and was able to monitor respiratory and cardiac rate, both in wearable solutions (chest and wrist) and in "invisible" solutions (office chair).Neste trabalho foram desenvolvidos e otimizados sensores em fibra ótica para aplicações biomédicas em soluções vestíveis e não intrusivas/ou invisíveis. Tendo em conta que se pretende que os dispositivos desenvolvidos não interfiram com os movimentos e o dia-a-dia do utilizador, os sensores de fibra ótica apresentam inúmeras vantagens quando comparados com os sensores eletrónicos convencionais, de entre várias, destacam-se: tamanho e peso reduzido, biocompatibilidade, segurança, imunidade a interferências eletromagnéticas e elevada sensibilidade. Numa primeira etapa, foram desenvolvidos dispositivos vestíveis com sensores de fibra ótica baseados em redes de Bragg (FBG) para incorporar em palmilhas de modo a monitorizar diferentes parâmetros da marcha com base na análise da pressão exercida em várias zonas da palmilha. Ainda no âmbito deste tema, adicionalmente, foram desenvolvidos sensores utilizando a mesma tecnologia de sensoriamento, mas capazes de monitorizar simultaneamente pressão e forças de cisalhamento. Este trabalho foi pioneiro e permitiu monitorizar um dos principais responsáveis pela ulceração dos pés em pessoas com diabetes: o cisalhamento. Numa fase posterior, o estudo centrou-se na temática relacionada com o aparecimento de úlceras em pessoas com mobilidade reduzida e utilizadores de cadeiras de rodas. De modo a contribuir para a mitigação deste flagelo, procurou-se desenvolver um sistema composto por uma rede de sensores de fibra ótica capaz de monitorizar a pressão em vários pontos de uma cadeira de rodas e não só aferir a pressão em cada ponto, mas monitorizar a postura do cadeirante e aconselhá-lo a mudar de postura com regularidade, de modo a diminuir a probabilidade de ocorrência desta patologia. Ainda dentro desta aplicação, foi publicado um outro trabalho onde o sensor não só monitoriza a pressão como também a temperatura em cada um dos pontos de análise, conseguindo aferir assim indiretamente o cisalhamento. Numa outra fase, foi realizado o estudo e desenvolvimento de sensores de fibra ótica de plástico para monitorizar a postura corporal de um utilizador de uma cadeira de escritório. Simultaneamente, foi desenvolvido um software capaz de monitorizar e mostrar ao utilizador todos os dados adquiridos em tempo real e advertir o utilizador de posturas incorretas, bem como aconselhar para pausas no trabalho. Numa quarta fase, o estudo centrou-se no desenvolvimento de sensores altamente sensíveis embebidos em materiais impressos 3D. O sensor é composto por uma fibra ótica com uma FBG e o corpo do sensor por um material polimérico flexível, denominado “Flexible”. O sensor foi impresso numa impressora 3D e durante a sua impressão foi incorporada a fibra ótica. O sensor demonstrou ser altamente sensível e foi capaz de monitorizar frequência respiratória e cardíaca, tanto em soluções vestíveis (peito e pulso) como em soluções “invisíveis” (cadeira de escritório).Programa Doutoral em Engenharia Físic

A multi-parametric wearable system to monitor neck movements and respiratory frequency of computer workers

Musculoskeletal disorders are the most common form of occupational ill-health. Neck pain is one of the most prevalent musculoskeletal disorders experienced by computer workers. Wrong postural habits and non-compliance of the workstation to ergonomics guidelines are the leading causes of neck pain. These factors may also alter respiratory functions. Health and safety interventions can reduce neck pain and, more generally, the symptoms of musculoskeletal disorders and reduce the consequent economic burden. In this work, a multi-parametric wearable system based on two fiber Bragg grating sensors is proposed for monitoring neck movements and breathing activity of computer workers. The sensing elements were positioned on the neck, in the frontal and sagittal planes, to monitor: (i) flexion-extension and axial rotation repetitions, and (ii) respiratory frequency. In this pilot study, five volunteers were enrolled and performed five repetitions of both flexion-extension and axial rotation, and ten breaths of both quite breathing and tachypnea. Results showed the good performances of the proposed system in monitoring the aforementioned parameters when compared to optical reference systems. The wearable system is able to well-match the trend in time of the neck movements (both flexion-extension and axial rotation) and to estimate mean and breath-by-breath respiratory frequency values with percentage errors ≤6.09% and ≤1.90%, during quiet breathing and tachypnea, respectively