Smart textile for respiratory monitoring and thoraco-abdominal motion pattern evaluation

Breathing Chest Wall Kinematics Assessment through a Single Digital Camera: A Feasibility Study

The identification of respiratory patterns based on the movement of the chest wall can assist in monitoring an individual's health status, particularly those with neuromuscular disorders, such as hemiplegia and Duchenne muscular dystrophy. Thoraco-abdominal asynchrony (TAA) refers to the lack of coordination between the rib cage and abdominal movements, characterized by a time delay in their expansion. Motion capture systems, like optoelectronic plethysmography (OEP), are commonly employed to assess these asynchronous movements. However, alternative technologies able to capture chest wall movements without physical contact, such as RGB digital cameras and time-of-flight digital cameras, can also be utilized due to their accessibility, affordability, and non-invasive nature. This study explores the possibility of using a single RGB digital camera to record the kinematics of the thoracic and abdominal regions by placing four non-reflective markers on the torso. In order to choose the positions of these markers, we previously investigated the movements of 89 chest wall landmarks using OEP. Laboratory tests and volunteer experiments were conducted to assess the viability of the proposed system in capturing the kinematics of the chest wall and estimating various time-related respiratory parameters (i.e., fR, Ti, Te, and Ttot) as well as TAA indexes. The results demonstrate a high level of agreement between the detected chest wall kinematics and the reference data. Furthermore, the system shows promising potential in estimating time-related respiratory parameters and identifying phase shifts indicative of TAA, thus suggesting its feasibility in detecting abnormal chest wall movements without physical contact with a single RGB camera.

Wearable Optical Fiber Sensors in Medical Monitoring Applications: A Review

Wearable optical fiber sensors have great potential for development in medical monitoring. With the increasing demand for compactness, comfort, accuracy, and other features in new medical monitoring devices, the development of wearable optical fiber sensors is increasingly meeting these requirements. This paper reviews the latest evolution of wearable optical fiber sensors in the medical field. Three types of wearable optical fiber sensors are analyzed: wearable optical fiber sensors based on Fiber Bragg grating, wearable optical fiber sensors based on light intensity changes, and wearable optical fiber sensors based on Fabry-Perot interferometry. The innovation of wearable optical fiber sensors in respiration and joint monitoring is introduced in detail, and the main principles of three kinds of wearable optical fiber sensors are summarized. In addition, we discuss their advantages, limitations, directions to improve accuracy and the challenges they face. We also look forward to future development prospects, such as the combination of wireless networks which will change how medical services are provided. Wearable optical fiber sensors offer a viable technology for prospective continuous medical surveillance and will change future medical benefits.

An IMU-Based Wearable System for Respiratory Rate Estimation in Static and Dynamic Conditions

PURPOSE

Breathing parameters change with activity and posture, but currently available solutions can perform measurements only during static conditions.

METHODS

This article presents an innovative wearable sensor system constituted by three inertial measurement units to simultaneously estimate respiratory rate (RR) in static and dynamic conditions and perform human activity recognition (HAR) with the same sensing principle. Two units are aimed at detecting chest wall breathing-related movements (one on the thorax, one on the abdomen); the third is on the lower back. All units compute the quaternions describing the subject's movement and send data continuously with the ANT transmission protocol to an app. The 20 healthy subjects involved in the research (9 men, 11 women) were between 23 and 54 years old, with mean age 26.8, mean height 172.5 cm and mean weight 66.9 kg. Data from these subjects during different postures or activities were collected and analyzed to extract RR.

RESULTS

Statistically significant differences between dynamic activities ("walking slow", "walking fast", "running" and "cycling") and static postures were detected (p < 0.05), confirming the obtained measurements are in line with physiology even during dynamic activities. Data from the reference unit only and from all three units were used as inputs to artificial intelligence methods for HAR. When the data from the reference unit were used, the Gated Recurrent Unit was the best performing method (97% accuracy). With three units, a 1D Convolutional Neural Network was the best performing (99% accuracy).

CONCLUSION

Overall, the proposed solution shows it is possible to perform simultaneous HAR and RR measurements in static and dynamic conditions with the same sensor system.

Investigating Stroke Effects on Respiratory Parameters Using a Wearable Device: A Pilot Study on Hemiplegic Patients

Quantitatively assessing personal health status is gaining increasing attention due to the improvement of diagnostic technology and the increasing occurrence of chronic pathologies. Monitoring physiological parameters allows for retrieving a general overview of the personal health status. Respiratory activity can provide relevant information, especially when pathologies affect the muscles and organs involved in breathing. Among many technologies, wearables may represent a valid solution for continuous and remote monitoring of respiratory activity, thus reducing healthcare costs. The most popular wearables used in this arena are based on detecting the breathing-induced movement of the chest wall. Therefore, their use in patients with impaired chest wall motion and abnormal respiratory kinematics can be challenging, but literature is still in its infancy. This study investigates the performance of a custom wearable device for respiratory monitoring in post-stroke patients. We tested the device on six hemiplegic patients under different respiratory regimes. The estimated respiratory parameters (i.e., respiratory frequency and the timing of the respiratory phase) demonstrated good agreement with the ones provided by a gold standard device. The promising results of this pilot study encourage the exploitation of wearables on these patients that may strongly impact the treatment of chronic diseases, such as hemiplegia.

Wearable Pressure Sensors for Pulse Wave Monitoring

Cardiovascular diseases remain the leading cause of death worldwide. The rapid development of flexible sensing technologies and wearable pressure sensors have attracted keen research interest and have been widely used for long-term and real-time cardiovascular status monitoring. Owing to compelling characteristics, including light weight, wearing comfort, and high sensitivity to pulse pressures, physiological pulse waveforms can be precisely and continuously monitored by flexible pressure sensors for wearable health monitoring. Herein, an overview of wearable pressure sensors for human pulse wave monitoring is presented, with a focus on the transduction mechanism, microengineering structures, and related applications in pulse wave monitoring and cardiovascular condition assessment. The conceptualizations and methods for the acquisition of physiological and pathological information related to the cardiovascular system are outlined. The biomechanics of arterial pulse waves and the working mechanism of various wearable pressure sensors, including triboelectric, piezoelectric, magnetoelastic, piezoresistive, capacitive, and optical sensors, are also subject to systematic debate. Exemple applications of pulse wave measurement based on microengineering structured devices are then summarized. Finally, a discussion of the opportunities and challenges that wearable pressure sensors face, as well as their potential as a wearable intelligent system for personalized healthcare is given in conclusion.

The Current State of Optical Sensors in Medical Wearables

Optical sensors play an increasingly important role in the development of medical diagnostic devices. They can be very widely used to measure the physiology of the human body. Optical methods include PPG, radiation, biochemical, and optical fiber sensors. Optical sensors offer excellent metrological properties, immunity to electromagnetic interference, electrical safety, simple miniaturization, the ability to capture volumes of nanometers, and non-invasive examination. In addition, they are cheap and resistant to water and corrosion. The use of optical sensors can bring better methods of continuous diagnostics in the comfort of the home and the development of telemedicine in the 21st century. This article offers a large overview of optical wearable methods and their modern use with an insight into the future years of technology in this field.

A Wearable System Composed of FBG-Based Soft Sensors for Trunk Compensatory Movements Detection in Post-Stroke Hemiplegic Patients

In this study, a novel wearable system for the identification of compensatory trunk movements (CTMs) in post-stroke hemiplegic patients is presented. The device is composed of seven soft sensing elements (SSEs) based on fiber Bragg grating (FBG) technology. Each SSE consists of a single FBG encapsulated into a flexible matrix to enhance the sensor’s robustness and improve its compliance with the human body. The FBG’s small size, light weight, multiplexing capability, and biocompatibility make the proposed wearable system suitable for multi-point measurements without any movement restriction. Firstly, its manufacturing process is presented, together with the SSEs’ mechanical characterization to strain. Results of the metrological characterization showed a linear response of each SSE in the operating range. Then, the feasibility assessment of the proposed system is described. In particular, the device’s capability of detecting CTMs was assessed on 10 healthy volunteers and eight hemiplegic patients while performing three tasks which are representative of typical everyday life actions. The wearable system showed good potential in detecting CTMs. This promising result may foster the use of the proposed device on post-stroke patients, aiming at assessing the proper course of the rehabilitation process both in clinical and domestic settings. Moreover, its use may aid in defining tailored strategies to improve post-stoke patients’ motor recovery and quality of life.

Electronic Textiles for Wearable Point-of-Care Systems

Traditional public health systems are suffering from limited, delayed, and inefficient medical services, especially when confronted with the pandemic and the aging population. Fusing traditional textiles with diagnostic, therapeutic, and protective medical devices can unlock electronic textiles (e-textiles) as point-of-care platform technologies on the human body, continuously monitoring vital signs and implementing round-the-clock treatment protocols in close proximity to the patient. This review comprehensively summarizes the research advances on e-textiles for wearable point-of-care systems. We start with a brief introduction to emphasize the significance of e-textiles in the current healthcare system. Then, we describe textile sensors for diagnosis, textile therapeutic devices for medical treatment, and textile protective devices for prevention, by highlighting their working mechanisms, representative materials, and clinical application scenarios. Afterward, we detail e-textiles' connection technologies as the gateway for real-time data transmission and processing in the context of 5G technologies and Internet of Things. Finally, we provide new insights into the remaining challenges and future directions in the field of e-textiles. Fueled by advances in chemistry and materials science, textile-based diagnostic devices, therapeutic devices, protective medical devices, and communication units are expected to interact synergistically to construct intelligent, wearable point-of-care textile platforms, ultimately illuminating the future of healthcare system in the Internet of Things era.

Application of textile technology in tissue engineering: A review

One of the key elements in tissue engineering is to design and fabricate scaffolds with tissue-like properties. Among various scaffold fabrication methods, textile technology has shown its unique advantages in mimicking human tissues' properties such as hierarchical, anisotropic, and strain-stiffening properties. As essential components in textile technology, textile patterns affect the porosity, architecture, and mechanical properties of textile-based scaffolds. However, the potential of various textile patterns has not been fully explored when fabricating textile-based scaffolds, and the effect of different textile patterns on scaffold properties has not been thoroughly investigated. This review summarizes textile technology development and highlights its application in tissue engineering to facilitate the broader application of textile technology, especially various textile patterns in tissue engineering. The potential of using different textile methods such as weaving, knitting, and braiding to mimic properties of human tissues is discussed, and the effect of process parameters in these methods on fabric properties is summarized. Finally, perspectives on future directions for explorations are presented. STATEMENT OF SIGNIFICANCE: Recently, biomedical engineers have applied textile technology to fabricate scaffolds for tissue engineering applications. Various textile methods, especially weaving, knitting, and braiding, enables engineers to customize the physical, mechanical, and biological properties of scaffolds. However, most textile-based scaffolds only use simple textile patterns, and the effect of different textile patterns on scaffold properties has not been thoroughly investigated. In this review, we cover for the first time the effect of process parameters in different textile methods on fabric properties, exploring the potential of using different textile methods to mimic properties of human tissues. Previous advances in textile technology are presented, and future directions for explorations are presented, hoping to facilitate new breakthroughs of textile-based tissue engineering.

Assessing the Tidal Volume through Wearables: A Scoping Review

The assessment of respiratory activity based on wearable devices is becoming an area of growing interest due to the wide range of available sensors. Accordingly, this scoping review aims to identify research evidence supporting the use of wearable devices to monitor the tidal volume during both daily activities and clinical settings. A screening of the literature (Pubmed, Scopus, and Web of Science) was carried out in December 2020 to collect studies: i. comparing one or more methodological approaches for the assessment of tidal volume with the outcome of a state-of-the-art measurement device (i.e., spirometry or optoelectronic plethysmography); ii. dealing with technological solutions designed to be exploited in wearable devices. From the initial 1031 documents, only 36 citations met the eligibility criteria. These studies highlighted that the tidal volume can be estimated by using different technologies ranging from IMUs to strain sensors (e.g., resistive, capacitive, inductive, electromagnetic, and optical) or acoustic sensors. Noticeably, the relative volumetric error of these solutions during quasi-static tasks (e.g., resting and sitting) is typically ≥10% but it deteriorates during dynamic motor tasks (e.g., walking). As such, additional efforts are required to improve the performance of these devices and to identify possible applications based on their accuracy and reliability.

Novel Real-Time OEP Phase Angle Feedback System for Dysfunctional Breathing Pattern Training-An Acute Intervention Study

Dysfunctional breathing patterns (DBP) can have an impact on an individual’s quality of life and/or exercise performance. Breathing retraining is considered to be the first line of treatment to correct breathing pattern, for example, reducing ribcage versus abdominal movement asynchrony. Optoelectronic plethysmography (OEP) is a non-invasive 3D motion capture technique that measures the movement of the chest wall. The purpose of this study was to investigate if the use of a newly developed real-time OEP phase angle and volume feedback system, as an acute breathing retraining intervention, could result in a greater reduction of phase angle values (i.e., an improvement in movement synchrony) when compared to real-time OEP volume feedback alone. Eighteen individuals with a DBP performed an incremental cycle test with OEP measuring chest wall movement. Participants were randomly assigned to either the control group, which included the volume-based OEP feedback or to the experimental group, which included both the volume-based and phase angle OEP feedback. Participants then repeated the same cycle test using the real-time OEP feedback. The phase angle between the ribcage versus abdomen (RcAbPhase), between the pulmonary ribcage and the combined abdominal ribcage and abdomen (RCpAbPhase), and between the abdomen and the shoulders (AbSPhase) were calculated during both cycle tests. Significant increases in RcAbPhase (pre: −2.89°, post: −1.39°, p < 0.01), RCpAbPhase (pre: −2.00°, post: −0.50°, p < 0.01), and AbSPhase (pre: −2.60°, post: −0.72°, p < 0.01) were found post-intervention in the experimental group. This indicates that the experimental group demonstrated improved synchrony in their breathing pattern and therefore, reverting towards a healthy breathing pattern. This study shows for the first time that dysfunctional breathing patterns can be acutely improved with real-time OEP phase angle feedback and provides interesting insight into the feasibility of using this novel feedback system for breathing pattern retraining in individuals with DBP.

A Home Telemedicine System for Continuous Respiratory Monitoring

This article presents a continuous home telemonitoring system for chronic respiratory patients using 5G connectivity developed in partnership with Vodafone as a part of the 5G Trial in Milan established by the Italian Ministry of Economic Development. The system features a wearable respiratory and activity monitor, an environmental sensor and a pulse oximeter sending the data through a 5G router to a Multi-Edge Computing server, incorporated in the Vodafone 5G infrastructure, where they are stored and accessible for visualization. In particular, activity, respiratory and environmental data are continuously streamed and collected. The solution has been tested on 18 healthy volunteers during non-supervised recordings lasting at least 48 hours. The combination of recognized activities and associated respiratory parameters provided statistically significant variations in breathing patterns between one activity and the other, thus giving more complete information to the clinicians than previously studied telemedicine systems based on spot-checks. In particular, statistically significant differences are found in tidal volume and minute ventilation between horizontal and vertical postures (p < 0.001) and between vertical postures and dynamic activities (p < 0.001); the respiratory rate shows statistically significant differences between horizontal and vertical postures (p < 0.001). Some environmental parameters have different mean values between day and night, such as carbon dioxide (p < 0.001). Trials on patients are needed to further study this telemedicine solution and make it commercially available in the future. The main further technical development suggested is the use of commercial 5G smartphones as routers, in order to make the system usable outside of home settings.

Wearable triboelectric sensors for biomedical monitoring and human-machine interface

A growing advocacy of healthy and quality life makes wearable electronics spring up. Triboelectric nanogenerator (TENG) has developed as an energy harvesting technology and as an advanced sensor technology in wearable electronics. The triboelectric sensor (TS) is sensitive to the mechanical motion and driven by the motion itself. Therefore, TS is capable of monitoring certain vital signs and kinds of movements of human body. Based on these monitoring, novel human-machine interfaces (HMIs) can be established. In this review, a comprehensive overview of some key progresses in this field over last 5 years are presented. Several main aspects of biomedical monitoring based on TSs are classified: pulse/cardiac/micro-motion, respiration/airflow/vibration, and pressure/tactile/body movement. The major types of HMIs taking these biomedical monitoring as basis are introduced accordingly: eye movement, voice/auditory, gesture/joint movement, and touch/tactile based HMIs. Finally, the current limitations and future trends are put forward for biomedical monitoring and HMIs based on TSs.

Verification of the Propagation Range of Respiratory Strain Using Signal Waveform Measured by FBG Sensors

The FBG (Fiber Bragg grating) sensor is an optical fiber type strain sensor. When a person breathes, strain occurs in the lungs and diaphragm. This was verified using an FBG sensor to which part of the living body this respiratory strain propagates. When measured in the abdomen, the signal waveforms were significantly different between breathing and apnea. The respiratory cycle measured by the temperature sensor attached to the mask and the strain cycle measured by the FBG sensor almost matched. Respiratory strain was measured in the abdomen, chest, and shoulder, and the signal amplitude decreased with distance from the abdomen. In addition, the respiratory rate could be calculated from the measured strain signal. On the other hand, respiratory strain did not propagate to the elbows and wrists, which were off the trunk, and the respiratory time, based on the signal period, could not be calculated at these parts. Therefore, it was shown that respiratory strain propagated in the trunk from the abdomen to the shoulder, but not in the peripheral parts of the elbow and wrist.

A Wearable Device for Breathing Frequency Monitoring: A Pilot Study on Patients with Muscular Dystrophy

Patients at risk of developing respiratory dysfunctions, such as patients with severe forms of muscular dystrophy, need a careful respiratory assessment, and periodic follow-up visits to monitor the progression of the disease. In these patients, at-home continuous monitoring of respiratory activity patterns could provide additional understanding about disease progression, allowing prompt clinical intervention. The core aim of the present study is thus to investigate the feasibility of using an innovative wearable device for respiratory monitoring, particularly breathing frequency variation assessment, in patients with muscular dystrophy. A comparison of measurements of breathing frequency with gold standard methods showed that the device based on the inertial measurement units (IMU-based device) provided optimal results in terms of accuracy errors, correlation, and agreement. Participants positively evaluated the device for ease of use, comfort, usability, and wearability. Moreover, preliminary results confirmed that breathing frequency is a valuable breathing parameter to monitor, at the clinic and at home, because it strongly correlates with the main indexes of respiratory function.

Comparison between the Airgo™ Device and a Metabolic Cart during Rest and Exercise

The aim of this study is to compare the accuracy of Airgo™, a non-invasive wearable device that records breath, with respect to a gold standard. In 21 healthy subjects (10 males, 11 females), four parameters were recorded for four min at rest and in different positions simultaneously by Airgo™ and SensorMedics 2900 metabolic cart. Then, a cardio-pulmonary exercise test was performed using the Erg 800S cycle ergometer in order to test Airgo™'s accuracy during physical effort. The results reveal that the relative error median percentage of respiratory rate was of 0% for all positions at rest and for different exercise intensities, with interquartile ranges between 3.5 (standing position) and 22.4 (low-intensity exercise) breaths per minute. During exercise, normalized amplitude and ventilation relative error medians highlighted the presence of an error proportional to the volume to be estimated. For increasing intensity levels of exercise, Airgo™'s estimate tended to underestimate the values of the gold standard instrument. In conclusion, the Airgo™ device provides good accuracy and precision in the estimate of respiratory rate (especially at rest), an acceptable estimate of tidal volume and minute ventilation at rest and an underestimation for increasing volumes.

A Wearable Device Based on a Fiber Bragg Grating Sensor for Low Back Movements Monitoring

Low back pain (LBP) is one of the musculoskeletal disorders that most affects workers. Among others, one of the working categories which mainly experiences such disease are video terminal workers. As it causes exploitation of the National Health Service and absenteeism in workplaces, LBP constitutes a relevant socio-economic burden. In such a scenario, a prompt detection of wrong seating postures can be useful to prevent the occurrence of this disorder. To date, many tools capable of monitoring the spinal range of motions (ROMs) are marketed, but most of them are unusable in working environments due to their bulkiness, discomfort and invasiveness. In the last decades, fiber optic sensors have made their mark allowing the creation of light and compact wearable systems. In this study, a novel wearable device embedding a Fiber Bragg Grating sensor for the detection of lumbar flexion-extensions (F/E) in seated subjects is proposed. At first, the manufacturing process of the sensing element was shown together with its mechanical characterization, that shows linear response to strain with a high correlation coefficient (R² > 0.99) and a sensitivity value (S_ε) of 0.20 nm∙mε⁻¹. Then, the capability of the wearable device in measuring F/E in the sagittal body plane was experimentally assessed on a small population of volunteers, using a Motion Capture system (MoCap) as gold standard showing good ability of the system to match the lumbar F/E trend in time. Additionally, the lumbar ROMs were evaluated in terms of intervertebral lumbar distances (ΔdL3−L1) and angles, exhibiting moderate to good agreement with the MoCap outputs (the maximum Mean Absolute Error obtained is ~16% in detecting ΔdL3−L1). The proposed wearable device is the first attempt for the development of FBG-based wearable systems for workers’ safety monitoring.

Smart Shirts for Monitoring Physiological Parameters: Scoping Review

BACKGROUND

The recent trends of technological innovation and widescale digitization as potential solutions to challenges in health care, sports, and emergency service operations have led to the conception of smart textile technology. In health care, these smart textile systems present the potential to aid preventative medicine and early diagnosis through continuous, noninvasive tracking of physical and mental health while promoting proactive involvement of patients in their medical management. In areas such as sports and emergency response, the potential to provide comprehensive and simultaneous physiological insights across multiple body systems is promising. However, it is currently unclear what type of evidence exists surrounding the use of smart textiles for the monitoring of physiological outcome measures across different settings.

OBJECTIVE

This scoping review aimed to systematically survey the existing body of scientific literature surrounding smart textiles in their most prevalent form, the smart shirt, for monitoring physiological outcome measures.

METHODS

A total of 5 electronic bibliographic databases were systematically searched (Ovid Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, Scopus, Cumulative Index to Nursing and Allied Health Literature, and SPORTDiscus). Publications from the inception of the database to June 24, 2019 were reviewed. Nonindexed literature relevant to this review was also systematically searched. The results were then collated, summarized, and reported.

RESULTS

Following the removal of duplicates, 7871 citations were identified. On the basis of title and abstract screening, 7632 citations were excluded, whereas 239 were retrieved and assessed for eligibility. Of these, 101 citations were included in the final analysis. Included studies were categorized into four themes: (1) prototype design, (2) validation, (3) observational, and (4) reviews. Among the 101 analyzed studies, prototype design was the most prevalent theme (50/101, 49.5%), followed by validation (29/101, 28.7%), observational studies (21/101, 20.8%), and reviews (1/101, 0.1%). Presented prototype designs ranged from those capable of monitoring one physiological metric to those capable of monitoring several simultaneously. In 29 validation studies, 16 distinct smart shirts were validated against reference technology under various conditions and work rates, including rest, submaximal exercise, and maximal exercise. The identified observational studies used smart shirts in clinical, healthy, and occupational populations for aims such as early diagnosis and stress detection. One scoping review was identified, investigating the use of smart shirts for electrocardiograph signal monitoring in cardiac patients.

CONCLUSIONS

Although smart shirts have been found to be valid and reliable in the monitoring of specific physiological metrics, results were variable for others, demonstrating the need for further systematic validation. Analysis of the results has also demonstrated gaps in knowledge, such as a considerable lag of validation and observational studies in comparison with prototype design and limited investigation using smart shirts in pediatric, elite sports, and emergency service populations.

Machine-knitted washable sensor array textile for precise epidermal physiological signal monitoring

Wearable textile electronics are highly desirable for realizing personalized health management. However, most reported textile electronics can either periodically target a single physiological signal or miss the explicit details of the signals, leading to a partial health assessment. Furthermore, textiles with excellent property and comfort still remain a challenge. Here, we report a triboelectric all-textile sensor array with high pressure sensitivity and comfort. It exhibits the pressure sensitivity (7.84 mV Pa^-1), fast response time (20 ms), stability (>100,000 cycles), wide working frequency bandwidth (up to 20 Hz), and machine washability (>40 washes). The fabricated TATSAs were stitched into different parts of clothes to monitor the arterial pulse waves and respiratory signals simultaneously. We further developed a health monitoring system for long-term and noninvasive assessment of cardiovascular disease and sleep apnea syndrome, which exhibits great advancement for quantitative analysis of some chronic diseases.

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.

Laser ablation in biliary tree: analysis of the intraductal and superficial thermal effects during the treatment

The treatment of choice for the unresectable cholangiocarcinoma is based on biliary decompression procedures. Despite stent placement is the standard of care, it is related to well-known complications. Hence, alternative techniques were proposed. Ideally, they should guarantee an adequate intraductal disobstruction, without injuring the surrounding tissues.This pre-clinical study aims to investigate the thermal effects of the laser ablation (LA) in the biliary tree, in terms of intraductal and surrounding tissue temperature achieved with different laser settings. The common bile ducts (in their upper and lower portions) of two pigs were ablated for 6 minutes with a diode laser at 3 W and 5 W. A custom-made laser applicator was used to obtain a circumferential ablation within the ducts. The intraductal temperature (T_id) was monitored by means of a fiber Bragg grating (FBG) sensor, while an infrared thermal camera monitored the T distribution in the surrounding tissues (T_sup). A maximum T difference of 65 °C and 57 °C was evidenced between the two power settings for the T_id measured in the upper and lower ducts, respectively. The mean difference between T_id and the averaged T_sup values was evaluated. At 5 W, a difference of 37±3 °C and 44±10 °C were obtained for the upper and lower ducts, respectively. At 3 W, a T difference of 2±1 °C was obtained for the upper biliary duct, while a difference of 8±1 °C was documented for the lower duct. Based on the results obtained in this preliminary study, the possibility to equip the laser probe with temperature sensor can improve the control and the safety of the procedure; this solution will guarantee the monitoring of the treatment while preserving the lumen and the surrounding structures.

A Contactless Respiratory Rate Estimation Method Using a Hermite Magnification Technique and Convolutional Neural Networks

The monitoring of respiratory rate is a relevant factor in medical applications and day-to-day activities. Contact sensors have been used mostly as a direct solution and they have shown their effectiveness, but with some disadvantages for example in vulnerable skins such as burns patients. For this reason, contactless monitoring systems are gaining increasing attention for respiratory detection. In this paper, we present a new non-contact strategy to estimate respiratory rate based on Eulerian motion video magnification technique using Hermite transform and a system based on a Convolutional Neural Network (CNN). The system tracks chest movements of the subject using two strategies: using a manually selected ROI and without the selection of a ROI in the image frame. The system is based on the classifications of the frames as an inhalation or exhalation using CNN. Our proposal has been tested on 10 healthy subjects in different positions. To compare performance of methods to detect respiratory rate the mean average error and a Bland and Altman analysis is used to investigate the agreement of the methods. The mean average error for the automatic strategy is 3.28 ± 3.33 % with and agreement with respect of the reference of ≈98%.

A Machine-Learning-Based Approach to Solve Both Contact Location and Force in Soft Material Tactile Sensors

This study addresses a design and calibration methodology based on numerical finite element method (FEM) modeling for the development of a soft tactile sensor able to simultaneously solve the magnitude and the application location of a normal load exerted onto its surface. The sensor entails the integration of a Bragg grating fiber optic sensor in a Dragon Skin 10 polymer brick (110 mm length, 24 mm width). The soft polymer mediates the transmission of the applied load to the buried fiber Bragg gratings (FBGs), and we also investigated the effect of sensor thickness on receptive field and sensitivity, both with the developed model and experimentally. Force-controlled indentations of the sensor (up to 2.5 N) were carried out through a cylindrical probe applied along the direction of the optical fiber (over an ∼90 mm span in length). A finite element model of the sensor was built and experimentally validated for 1 and 6 mm thicknesses of the soft polymeric encapsulation material, considering that the latter thickness resulted from numerical simulations as leading to optimal cross talk and sensitivity, given the chosen soft material. The FEM model was also used to train a neural network so as to obtain the inverse sensor function. Using four FBG transducers embedded in the 6-mm-thick soft polymer, the proposed machine learning approach managed to accurately detect both load magnitude (R = 0.97) and location (R = 0.99) over the whole experimental range. The proposed system could be used for developing tactile sensors that can be effectively used for a broad range of applications.

Wearable systems for shoulder kinematics assessment: a systematic review

BACKGROUND

Wearable sensors are acquiring more and more influence in diagnostic and rehabilitation field to assess motor abilities of people with neurological or musculoskeletal impairments. The aim of this systematic literature review is to analyze the wearable systems for monitoring shoulder kinematics and their applicability in clinical settings and rehabilitation.

METHODS

A comprehensive search of PubMed, Medline, Google Scholar and IEEE Xplore was performed and results were included up to July 2019. All studies concerning wearable sensors to assess shoulder kinematics were retrieved.

RESULTS

Seventy-three studies were included because they have fulfilled the inclusion criteria. The results showed that magneto and/or inertial sensors are the most used. Wearable sensors measuring upper limb and/or shoulder kinematics have been proposed to be applied in patients with different pathological conditions such as stroke, multiple sclerosis, osteoarthritis, rotator cuff tear. Sensors placement and method of attachment were broadly heterogeneous among the examined studies.

CONCLUSIONS

Wearable systems are a promising solution to provide quantitative and meaningful clinical information about progress in a rehabilitation pathway and to extrapolate meaningful parameters in the diagnosis of shoulder pathologies. There is a strong need for development of this novel technologies which undeniably serves in shoulder evaluation and therapy.

Wearable textile based on silver plated knitted sensor for respiratory rate monitoring

Wearable systems are gaining broad acceptance for monitoring physiological parameters in several medical applications. Among a number of approaches, smart textiles have attracted interest because they are comfortable and do not impair patients' movements. In this article, we aim at developing a smart textile for respiratory monitoring based on a piezoresistive sensing element. Firstly, the calibration curve of the system and its hysteresis have been investigated. Then, the proposed system has been assessed on 6 healthy subjects. The volunteers were invited to wear the system to monitor their breathing rate. The results of the calibration show a good mean sensitivity (i.e., approximately 0.11V·%^-1); although the hysteresis is not negligible, the system can follow the cycles also at high rates (up to 36 cycle·min^-1). The feasibility assessment on 6 volunteers (two trials for each one) shows that the proposed system can estimate with good accuracy the breathing rate. Indeed, the results obtained by the proposed system were compared with the ones collected with a spirometer, used as reference. Considering all the experiments, a mean percentage error was approximately 2%. In conclusion, the proposed system has several valuable features (e.g., the sensing element is lightweight, the sensitivity is high, and it is possible to develop comfortable smart textile); in addition, the promising performances considering both metrological properties and assessment on volunteers foster future tests focused on: i) the possibility of developing and system embedding several sensing elements, and ii) to develop a wireless acquisition system, to allow comfortable and long-term acquisition in both patients and during sport activities.

Polymer-coated fiber optic probe for the monitoring of breathing pattern and respiratory rate

In recent years, no-invasive and small size systems are meeting the demand of the new healthcare system, in which the vital signs monitoring is gaining in importance. In this context, Fiber Bragg grating (FBG) sensors are becoming very popular and FBG-based systems could be used for monitoring vital signs. At the same time, FBG could be able to sense chemical parameters by the polymer functionalization. The aim of our study was investigating the ability of a polymer-coated FBG-based probe for monitoring breathing patterns and respiratory rates. We tested the proposed FBG-based probe on 9 healthy volunteers during spirometry, the most common pulmonary function test. Results showed the high accuracy of the proposed probe to detect respiratory rate. The comparison between the respiratory rates estimated by the probe with the ones by the spirometer showed the absolute value of the percentage errors lower than 2.07% (in the 78% of cases <.91%). Lastly, a Bland Altman analysis was performed to compare the instantaneous respiratory rate values gathered by the spirometer and the FBG probe showing the feasibility of breath-by-breath monitoring by the proposed probe. Results showed a bias of 0.06± 2.90 $\mathrm{breaths}\square {\mathrm {min}}^{-1}$. Additionally, our system was able to follow the breathing activities and monitoring the breathing patterns.

E-Textiles for Healthy Ageing

The ageing population has grown quickly in the last half century with increased longevity and declining birth rate. This presents challenges to health services and the wider society. This review paper considers different aspects (e.g., physical, mental, and social well-being) of healthy ageing and how health devices can help people to monitor health conditions, treat diseases and promote social interactions. Existing technologies for addressing non-physical (e.g., Alzheimer's, loneliness) and physical (e.g., stroke, bedsores, and fall) related challenges are presented together with the drivers and constraints of using e-textiles for these applications. E-textiles provide a platform that enables unobtrusive and ubiquitous deployment of sensors and actuators for healthy ageing applications. However, constraints remain on battery, integration, data accuracy, manufacturing, durability, ethics/privacy issues, and regulations. These challenges can only effectively be met by interdisciplinary teams sharing expertise and methods, and involving end users and other key stakeholders at an early stage in the research.

Diaphragm-based optical fiber sensor for pulse wave monitoring and cardiovascular diseases diagnosis

Arterial pulse wave has been considered as a vital sign in assessment of cardiovascular diseases. Noninvasive pulse sensor with compact structure, immunity to electro-magnetic interference and high sensitivity is the research focus in recent years. While, optical fiber biosensor is a competitive option to meet these needs. Here, a diaphragm-based optical fiber pulse sensor was proposed to achieve high-precision radial pulse wave monitoring. A wearable device was developed, composed of a sports wristband and an aluminum diaphragm-based optical fiber sensor tip of only 1 cm in diameter, which was highly sensitive to the weak acoustic signal. In particular, coherent phase detection was adopted to improve detection signal-to-noise ratio, so as to recover the high-fidelity pulse waveforms. A clinical experiment was carried out to detect and morphological analyze the pulse waveforms of four subjects, the results of which preliminarily demonstrated the feasibility of pulse diagnosis method. The proposed pulse fiber sensor provides a comfortable way for pulse diagnosis, which is promising in early cardiovascular diseases indicating.

Recent development of respiratory rate measurement technologies

Respiratory rate (RR) is an important physiological parameter whose abnormality has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to perform, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies.

Non-Contact Monitoring of Breathing Pattern and Respiratory Rate via RGB Signal Measurement

Among all the vital signs, respiratory rate remains the least measured in several scenarios, mainly due to the intrusiveness of the sensors usually adopted. For this reason, all contactless monitoring systems are gaining increasing attention in this field. In this paper, we present a measuring system for contactless measurement of the respiratory pattern and the extraction of breath-by-breath respiratory rate. The system consists of a laptop’s built-in RGB camera and an algorithm for post-processing of acquired video data. From the recording of the chest movements of a subject, the analysis of the pixel intensity changes yields a waveform indicating respiratory pattern. The proposed system has been tested on 12 volunteers, both males and females seated in front of the webcam, wearing both slim-fit and loose-fit t-shirts. The pressure-drop signal recorded at the level of nostrils with a head-mounted wearable device was used as reference respiratory pattern. The two methods have been compared in terms of mean of absolute error, standard error, and percentage error. Additionally, a Bland–Altman plot was used to investigate the bias between methods. Results show the ability of the system to record accurate values of respiratory rate, with both slim-fit and loose-fit clothing. The measuring system shows better performance on females. Bland–Altman analysis showed a bias of −0.01 breaths·min−1, with respiratory rate values between 10 and 43 breaths·min−1. Promising performance has been found in the preliminary tests simulating tachypnea.

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Individuals with a Speech Disability

High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for individuals with a speech disability, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain–computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user’s environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications.

Contact-Based Methods for Measuring Respiratory Rate

There is an ever-growing demand for measuring respiratory variables during a variety of applications, including monitoring in clinical and occupational settings, and during sporting activities and exercise. Special attention is devoted to the monitoring of respiratory rate because it is a vital sign, which responds to a variety of stressors. There are different methods for measuring respiratory rate, which can be classed as contact-based or contactless. The present paper provides an overview of the currently available contact-based methods for measuring respiratory rate. For these methods, the sensing element (or part of the instrument containing it) is attached to the subject's body. Methods based upon the recording of respiratory airflow, sounds, air temperature, air humidity, air components, chest wall movements, and modulation of the cardiac activity are presented. Working principles, metrological characteristics, and applications in the respiratory monitoring field are presented to explore potential development and applicability for each method.

Influence of polyester spacer fabric, cotton, chloroprene rubber, and silicone on microclimatic and morphologic physiologic skin parameters in vivo

BACKGROUND

Skin diseases can develop upon disadvantageous microclimate in relation to skin contact with textiles of supporting devices. Increased temperature, moisture, mechanical fracture, pressure, and inflammatory processes often occur mutually and enhance each other in their adverse effects. Therefore, the early prevention of skin irritations by improvement of microclimatic properties of skin in contact with supporting devices is important.

MATERIALS AND METHODS

In this study, the microclimate under occlusion with polyester, cotton, chloroprene rubber, and silicone textiles, used for supporting devices, was analyzed by determining several characteristic physiologic skin parameters in vivo, including temperature, moisture, and transepidermal water loss (TEWL). This is achieved by comparing a miniaturized in vivo detection device with several established optical and sensory methods in vivo.

RESULTS

A highly significant TEWL decrease was found after polyester, chloroprene rubber, and silicone application. The application of all materials showed highly significant decrease in skin surface temperature, with chloroprene rubber showing the lowest. Similarly, all materials showed highly significant increase in relative moisture, where the highest increase was found for chloroprene rubber and silicone and the lowest increase for cotton. The cutaneous carotenoid concentration of chloroprene rubber, silicone, and polyester decreased. A manipulation of the surface structure of the stratum corneum was recognized for all materials except for cotton by laser scanning microscopy.

CONCLUSION

The skin parameters temperature, relative moisture, antioxidant status, and TEWL can effectively characterize the microclimatic environment during occlusion with medical supporting materials. These parameters could potentially be used to develop standardized testing procedures for material evaluation.

Breathing Pattern Interpretation as an Alternative and Effective Voice Communication Solution

Augmentative and alternative communication (AAC) systems tend to rely on the interpretation of purposeful gestures for interaction. Existing AAC methods could be cumbersome and limit the solutions in terms of versatility. The study aims to interpret breathing patterns (BPs) to converse with the outside world by means of a unidirectional microphone and researches breathing-pattern interpretation (BPI) to encode messages in an interactive manner with minimal training. We present BP processing work with (1) output synthesized machine-spoken words (SMSW) along with single-channel Weiner filtering (WF) for signal de-noising, and (2) k-nearest neighbor (k-NN) classification of BPs associated with embedded dynamic time warping (DTW). An approved protocol to collect analogue modulated BP sets belonging to 4 distinct classes with 10 training BPs per class and 5 live BPs per class was implemented with 23 healthy subjects. An 86% accuracy of k-NN classification was obtained with decreasing error rates of 17%, 14%, and 11% for the live classifications of classes 2, 3, and 4, respectively. The results express a systematic reliability of 89% with increased familiarity. The outcomes from the current AAC setup recommend a durable engineering solution directly beneficial to the sufferers.

Development of an electrochemical surface-enhanced Raman spectroscopy (EC-SERS) fabric-based plasmonic sensor for point-of-care diagnostics

A plasmonic fabric-based electrode has been developed for wearable EC-SERS sensing for point-of-care applications.