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

Smart vest for respiratory rate monitoring of COPD patients based on non-contact capacitive sensing

In this paper, a first approach to the design of a portable device for non-contact monitoring of respiratory rate by capacitive sensing is presented. The sensing system is integrated into a smart vest for an untethered, low-cost and comfortable breathing monitoring of Chronic Obstructive Pulmonary Disease (COPD) patients during the rest period between respiratory rehabilitation exercises at home. To provide an extensible solution to the remote monitoring using this sensor and other devices, the design and preliminary development of an e-Health platform based on the Internet of Medical Things (IoMT) paradigm is also presented. In order to validate the proposed solution, two quasi-experimental studies have been developed, comparing the estimations with respect to the golden standard. In a first study with healthy subjects, the mean value of the respiratory rate error, the standard deviation of the error and the correlation coefficient were 0.01 breaths per minute (bpm), 0.97 bpm and 0.995 (p < 0.00001), respectively. In a second study with COPD patients, the values were -0.14 bpm, 0.28 bpm and 0.9988 (p < 0.0000001), respectively. The results for the rest period show the technical and functional feasibility of the prototype and serve as a preliminary validation of the device for respiratory rate monitoring of patients with COPD.Ministerio de Ciencia e Innovación PI15/00306Ministerio de Ciencia e Innovación DTS15/00195Junta de Andalucía PI-0010-2013Junta de Andalucía PI-0041-2014Junta de Andalucía PIN-0394-201

Design and development of a wearable inductive textile sensor to monitor back movements

This thesis focuses on the design and development of a wireless and wearable platform that employs an inductive sensor to track trunk movements when the user bends forward. The inductive textile sensor was designed based on the anthropometrical dimensions of the trunk’s lumbar area of a healthy female. The chosen shape of the sensor was a rectangular flat coil. The inductance behavior was investigated using theoretical calculations and simulations. Formulas developed by Grover and Terman were used to calculate the inductance to validate the inductive textile design. The simulations were used to analyze the change of the inductance when the area, perimeter, height, and width of the rectangle was modified, as well as the effect of the number of turns of the rectangular flat coil. Results from the theoretical calculations and simulations were compared. The inductive textile sensor was integrated at the lumbar section of a sleeveless garment to create a smart wearable platform. The performance of the smart garment was evaluated experimentally on a healthy participant, and it was shown that the designed sensor can detect forward bending movements. The evaluation scenario was further extended to also include twisting and lateral bending of the trunk, and it was observed that the proposed design can successfully discriminate such movements from forward bending of the trunk. An interference test showed that, although moving a cellphone towards the unworn prototype affected the sensor readings, manipulating the cellphone when wearing the prototype, did not compromise the capability of the sensor to detect forward bends. The proposed platform is a promising step towards developing wearable systems to monitor back posture to prevent or treat low back pain associated with poor posture

Towards the internet of smart clothing: a review on IoT wearables and garments for creating intelligent connected e-textiles

[Abstract] Technology has become ubiquitous, it is all around us and is becoming part of us. Togetherwith the rise of the Internet of Things (IoT) paradigm and enabling technologies (e.g., Augmented Reality (AR), Cyber-Physical Systems, Artificial Intelligence (AI), blockchain or edge computing), smart wearables and IoT-based garments can potentially have a lot of influence by harmonizing functionality and the delight created by fashion. Thus, smart clothes look for a balance among fashion, engineering, interaction, user experience, cybersecurity, design and science to reinvent technologies that can anticipate needs and desires. Nowadays, the rapid convergence of textile and electronics is enabling the seamless and massive integration of sensors into textiles and the development of conductive yarn. The potential of smart fabrics, which can communicate with smartphones to process biometric information such as heart rate, temperature, breathing, stress, movement, acceleration, or even hormone levels, promises a new era for retail. This article reviews the main requirements for developing smart IoT-enabled garments and shows smart clothing potential impact on business models in the medium-term. Specifically, a global IoT architecture is proposed, the main types and components of smart IoT wearables and garments are presented, their main requirements are analyzed and some of the most recent smart clothing applications are studied. In this way, this article reviews the past and present of smart garments in order to provide guidelines for the future developers of a network where garments will be connected like other IoT objects: the Internet of Smart Clothing.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED341D R2016/012Xunta de Galicia; ED431G/01Agencia Estatal de Investigación de España; TEC2013-47141-C4-1-RAgencia Estatal de Investigación de España; TEC2016-75067-C4-1-RAgencia Estatal de Investigación de España; TEC2015-69648-RED

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

Defining Requirements and Related Methods for Designing Sensorized Garments

Designing smart garments has strong interdisciplinary implications, specifically related to user and technical requirements, but also because of the very different applications they have: medicine, sport and fitness, lifestyle monitoring, workplace and job conditions analysis, etc. This paper aims to discuss some user, textile, and technical issues to be faced in sensorized clothes development. In relation to the user, the main requirements are anthropometric, gender-related, and aesthetical. In terms of these requirements, the user’s age, the target application, and fashion trends cannot be ignored, because they determine the compliance with the wearable system. Regarding textile requirements, functional factors—also influencing user comfort—are elasticity and washability, while more technical properties are the stability of the chemical agents’ effects for preserving the sensors’ efficacy and reliability, and assuring the proper duration of the product for the complete life cycle. From the technical side, the physiological issues are the most important: skin conductance, tolerance, irritation, and the effect of sweat and perspiration are key factors for reliable sensing. Other technical features such as battery size and duration, and the form factor of the sensor collector, should be considered, as they affect aesthetical requirements, which have proven to be crucial, as well as comfort and wearability

A real-time posture monitoring system towards bad posture detection

The neck and back pains are the most spread health problems of the century caused by remaining slouching for long hours on the smart phones, the tablets and the computers. Many medical researches prove that the monitoring and the improving of the seating posture can prevent the spinal pains. In this paper we propose a Real-time seating posture monitoring system. The system is composed of a smart belt equipped with inertial sensors. The sensors collect the posture information and send them to a cloud server via Wi-Fi connection. The cloud server processes the collected data, then, sends the result to mobile applications via Wi-Fi connection. The mobile applications allow the user to monitor his posture over time and receive in Real-time a sound and a visual notification in case of a bad posture detection. Two mobile applications Android and iOS are implemented that can be used for different mobile phone OS. In this work we will detail the design and the architecture of the proposed posture monitoring system and the implemented mobile applications. We will present the posture measurements of good and bad posture using the proposed posture monitoring system

Estimating posture-recognition performance in sensing garments using geometric wrinkle modeling

A fundamental challenge limiting information quality obtained from smart sensing garments is the influence of textile movement relative to limbs. We present and validate a comprehensive modeling and simulation framework to predict recognition performance in casual loose-fitting garments. A statistical posture and wrinkle-modeling approach is introduced to simulate sensor orientation errors pertained to local garment wrinkles. A metric was derived to assess fitting, the body-garment mobility. We validated our approach by analyzing simulations of shoulder and elbow rehabilitation postures with respect to experimental data using actual casual garments. Results confirmed congruent performance trends with estimation errors below 4% for all study participants. Our approach allows to estimate the impact of fitting before implementing a garment and performing evaluation studies with it. These simulations revealed critical design parameters for garment prototyping, related to performed body posture, utilized sensing modalities, and garment fitting. We concluded that our modeling approach can substantially expedite design and development of smart garments through early-stage performance analysis