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.

Wearable systems are gaining large interest in applications related to the monitoring of physiological parameters. Piezoresistive strain sensors are a valid option to develop wearables for several medical applications. Among them, respiratory monitoring can be performed by recording chest movements. The aim of this study is threefold: (i) the experimental assessment of elastic piezoresistive textile; (ii) the influence of length and width on piezoresistive response; (iii) the use of these elements to develop a smart textile (ST) for respiratory monitoring. The ST consists of six piezoresistive elements. The static calibration and the hysteresis analysis were carried out to assess the characteristics of the piezoresistive elements. The feasibility assessment of the ST for respiratory monitoring was performed on 4 healthy volunteers under two conditions (i.e., quiet breathing and tachypnea). Respiratory frequency values were estimated by the ST and compared to the ones gathered by means of a reference system (i.e., a motion capture system). Length and width influence both sensitivity and hysteresis of the piezoresistive element. Regarding the ST performance, good agreement with data provided by the reference system was found. Indeed, results obtained by considering the output of single sensing elements and their sum were promising: the difference between the average respiratory frequency was always lower than 1% and 4% during quiet breathing and tachypnea, respectively. The proposed ST seems to be suitable for respiratory frequency monitoring in a wide range of values, where unobtrusiveness is of great value.

Unobtrusive and wearable devices are gaining large acceptance in the continuous monitoring of physiological parameters. Among the five vital signs, respiratory rate (fR) can be used to detect physiological abnormalities and health status changes. The purpose of this work was to investigate the performances of a multi-sensor smart garment in estimating the fR during walking and running activities. Bespoke algorithms have been implemented to retrieve fR values from raw data. Experiments were carried out on ten male volunteers during walking and running activities at selected speeds controlled by a treadmill (i.e., from 1.6 km.h-1 to 8.0 km.h-1). Data were analysed in both frequency and time domains. In the frequency domain, fR was analyzed considering a time window of 20 s. The 97% of fR estimated by the garment agreed with the reference (i.e., flowmeter) values in the range 13 breaths per minute (bpm). In the time domain, breath-by-breath fR analysis was carried out. The garment performance was evaluated in terms of mean absolute error (MAE), standard error (SE),mean percentage error (mean %E[i]) and by the Bland-Altman analysis. Good agreement with the reference device was testified by low MAE (<1.86 bpm), SE (<0.21 bpm), mean %E[i] (<2.83 ), and by the Bland-Altman analysis (Mean of Differences = 0.22 bpm, Limits of Agreement = 6.06 bpm). Summing up, the garment based on six sensing elements and related bespoke algorithms are able to provide robust information about fR on both average and breath-by-breath bases even during physical activities.

There is a growing demand of comfortable and unobtrusive wearable systems for monitoring a variety of physiological parameters and in particular the respiratory frequency (fR). The most popular techniques for fR monitoring cannot be used in several clinical applications and in unstructured environment. These issues have fostered a dramatic growth of interest for wearable systems devoted to monitor fR. In this arena, fiber Bragg grating (FBG) sensors have gained due to a variety of benefits. In this work, we designed and fabricated an FBG-based wearable device for fR monitoring from the nasal airflow. The proposed design does not require a mask to improve the comfortability and acceptability of the system. The sensing element was functionalized by a hygroscopic coating material to make the FBG sensitive to relative humidity changes. This feature allows calculating fR starting from the discrimination between the inspiration and expiration phases. A pilot study on 6 volunteers was designed to assess the system during three different breathing stages (i.e., slow, normal and fast breathing). Results showed high performance of the proposed wearable device in detecting mean and breath-by-breath fR values (i.e., mean percentage errors ≤ 2.29 % and bias ≤ 0.31 breaths per minute) during slow breathing, normal breathing, and fast breathing.

Workers experiencing high levels of stress may suffer from poor motivation, low level of attention, and physical disorders which, in turn, may lead to work injuries. Respiratory frequency (f _R ) is considered one of the most reliable indicators of the mental load and fatigue state of workers. Monitoring this parameter through wearable devices represents an efficient solution for the maintenance of Occupational Health and Safety. We developed an innovative wearable system equipped with flexible sensors based on fiber Bragg gratings (FBGs) to monitor f _R in static and dynamic conditions characterizing occupational settings. This article provides a description of the system and of the metrological characteristics of the flexible sensors in terms of response to strain and temperature changes, and hysteresis error. The performances of the device, evaluated in a laboratory during the execution of tasks mimicking real work activity, are also reported. The obtained promising results encourage the engineering of the system for use in real workplaces to collect quantitative information on the psychophysical state of workers and its relation to stress level.

The continuous and simultaneous monitoring of physiological parameters represents a key aspect in clinical environments, remote monitoring and occupational settings. In this regard, respiratory rate (RR) and heart rate (HR) are correlated with several physiological and pathological conditions of the patients/workers, and with environmental stressors. In this work, we present and validate a wearable device for the continuous monitoring of such parameters. The proposed system embeds four conductive sensors located on the user’s chest which allow retrieving the breathing activity through their deformation induced during cyclic expansion and contraction of the rib cage. For monitoring HR we used an embedded IMU located on the left side of the chest wall. We compared the proposed device in terms of estimating HR and RR against a reference system in three scenarios: sitting, standing and supine. The proposed system reliably estimated both RR and HR, showing low error averaged along subjects in all scenarios. This is the first study focused on the feasibility assessment of a wearable system based on a multi-sensor configuration (i.e., conductive sensors and IMU) for RR and HR monitoring. The promising results encourage the application of this approach in clinical and occupational settings.