Flexible Textile Sensors-Based Smart T-Shirt for Respiratory Monitoring: Design, Development, and Preliminary Validation.

Respiratory rate (fR) monitoring through wearable devices is crucial in several scenarios, providing insights into well-being and sports performance while minimizing interference with daily activities. Strain sensors embedded into garments stand out but require thorough investigation for optimal deployment. Optimal sensor positioning is often overlooked, and when addressed, the quality of the respiratory signal is neglected. Additionally, sensor metrological characterization after sensor integration is often omitted. In this study, we present the design, development, and feasibility assessment of a smart t-shirt embedded with two flexible sensors for fR monitoring. Guided by a motion capture system, optimal sensor design and position on the chest wall were defined, considering both signal magnitude and quality. The sensors were developed, embedded into the wearable system, and metrologically characterized, demonstrating a remarkable response to both static (sensitivity 9.4 Ω⋅%-1 and 9.1 Ω⋅%-1 for sensor A and sensor B, respectively) and cyclic loads (min. hysteresis span 20.4% at 36 bpm obtained for sensor A). The feasibility of the wearable system was assessed on healthy volunteers both under static and dynamic conditions (such as running, walking, and climbing stairs). A mean absolute error of 0.32 bpm was obtained by averaging all subjects and tests using the combination of the two sensors. This value was lower than that obtained using both sensor A (0.53 bpm) and sensor B (0.78 bpm) individually. Our study highlights the importance of signal amplitude and quality in optimal sensor placement evaluation, as well as the characterization of the embedded sensors for metrological assessment.

Flexible Matrices for the Encapsulation of Plant Wearable Sensors: Influence of Geometric and Color Features on Photosynthesis and Transpiration.

The safeguarding of plant health is vital for optimizing crop growth practices, especially in the face of the biggest challenges of our generation, namely the environmental crisis and the dramatic changes in the climate. Among the many innovative tools developed to address these issues, wearable sensors have recently been proposed for monitoring plant growth and microclimates in a sustainable manner. These systems are composed of flexible matrices with embedded sensing elements, showing promise in revolutionizing plant monitoring without being intrusive. Despite their potential benefits, concerns arise regarding the effects of the long-term coexistence of these devices with the plant surface. Surprisingly, a systematic analysis of their influence on plant physiology is lacking. This study aims to investigate the effect of the color and geometric features of flexible matrices on two key plant physiological functions: photosynthesis and transpiration. Our findings indicate that the negative effects associated with colored substrates, as identified in recent research, can be minimized by holing the matrix surface with a percentage of voids of 15.7%. This approach mitigates interference with light absorption and reduces water loss to a negligible extent, making our work one of the first pioneering efforts in understanding the intricate relationship between plant wearables' features and plant health.

Optimizing Sensor Placement for Temperature Mapping during Ablation Procedures.

Accurately mapping the temperature during ablation is crucial for improving clinical outcomes. While various sensor configurations have been suggested in the literature, depending on the sensors' type, number, and size, a comprehensive understanding of optimizing these parameters for precise temperature reconstruction is still lacking. This study addresses this gap by introducing a tool based on a theoretical model to optimize the placement of fiber Bragg grating sensors (FBG) within the organ undergoing ablation. The theoretical model serves as a general framework, allowing for adaptation to various situations. In practical application, the model provides a foundational structure, with the flexibility to tailor specific optimal solutions by adjusting problem-specific data. We propose a nonlinear and nonconvex (and, thus, only solvable in an approximated manner) optimization formulation to determine the optimal distribution and three-dimensional placement of FBG arrays. The optimization aims to find a trade-off among two objectives: maximizing the variance of the expected temperatures measured by the sensors, which can be obtained from a predictive simulation that considers both the type of applicator used and the specific organ involved, and maximizing the squared sum of the distances between the sensor pairs. The proposed approach provides a trade-off between collecting diverse temperatures and not having all the sensors concentrated in a single area. We address the optimization problem through the utilization of approximation schemes in programming. We then substantiate the efficacy of this approach through simulations. This study tackles optimizing the FBGs' sensor placement for precise temperature monitoring during tumor ablation. Optimizing the FBG placement enhances temperature mapping, aiding in tumor cell eradication while minimizing damage to surrounding tissues.

Breathing Motion Pattern in Cyclists: Role of Inferior against Superior Thorax Compartment.

The thoracoabdominal breathing motion pattern is being considered in sports training because of its contribution, along with other physiological adaptations, to overall performance. We examined whether and how experience with cycling training modifies the thoracoabdominal motion patterns. We utilized optoelectronic plethysmography to monitor ten trained male cyclists and compared them to ten physically active male participants performing breathing maneuvers. Cyclists then participated in a self-paced time trial to explore the similarity between that observed during resting breathing. From the 3D coordinates of 32 markers positioned on each participant's trunk, we calculated the percentage of contribution of the superior thorax, inferior thorax, and abdomen and the correlation coefficient among these compartments. During the rest maneuvers, the cyclists showed a thoracoabdominal motion pattern characterized by an increased role of the inferior thorax relative to the superior thorax (26.69±5.88%, 34.93±5.03%; p=0.002, respectively), in contrast to the control group (26.69±5.88%; 25.71±6.04%, p=0.4, respectively). In addition, the inferior thorax showed higher coordination in phase with the abdomen. Furthermore, the results of the time trial test underscored the same pattern found in cyclists breathing at rest, suggesting that the development of a permanent modification in respiratory mechanics may be associated with cycling practice.

Wearable Systems for Unveiling Collective Intelligence in Clinical Settings.

Nowadays, there is an ever-growing interest in assessing the collective intelligence (CI) of a team in a wide range of scenarios, thanks to its potential in enhancing teamwork and group performance. Recently, special attention has been devoted on the clinical setting, where breakdowns in teamwork, leadership, and communication can lead to adverse events, compromising patient safety. So far, researchers have mostly relied on surveys to study human behavior and group dynamics; however, this method is ineffective. In contrast, a promising solution to monitor behavioral and individual features that are reflective of CI is represented by wearable technologies. To date, the field of CI assessment still appears unstructured; therefore, the aim of this narrative review is to provide a detailed overview of the main group and individual parameters that can be monitored to evaluate CI in clinical settings, together with the wearables either already used to assess them or that have the potential to be applied in this scenario. The working principles, advantages, and disadvantages of each device are introduced in order to try to bring order in this field and provide a guide for future CI investigations in medical contexts.

A review on radiofrequency, laser, and microwave ablations and their thermal monitoring through fiber Bragg gratings.

Thermal ablation of tumors aims to apply extreme temperatures inside the target tissue to achieve substantial tumor destruction in a minimally invasive manner. Several techniques are comprised, classified according to the type of energy source. However, the lack of treatment selectivity still needs to be addressed, potentially causing two risks: i) incomplete tumor destruction and recurrence, or conversely, ii) damage of the surrounding healthy tissue. Therefore, the research herein reviewed seeks to develop sensing systems based on fiber Bragg gratings (FBGs) for thermal monitoring inside the lesion during radiofrequency, laser, and microwave ablation. This review shows that, mainly thanks to multiplexing and minimal invasiveness, FBGs provide an optimal sensing solution. Their temperature measurements are the feedback to control the ablation process and allow to investigate different treatments, compare their outcomes, and quantify the impact of factors such as proximity to thermal probe and blood vessels, perfusion, and tissue type.

Current and future technologies for monitoring cultured meat: A review.

The high population growth rate, massive animal food consumption, fast economic progress, and limited food resources could lead to a food crisis in the future. There is a huge requirement for dietary proteins including cultured meat is being progressed to fulfill the need for meat-derived proteins in the diet. However, production of cultured meat requires monitoring numerous bioprocess parameters. This review presents a comprehensive overview of various widely adopted techniques (optical, spectroscopic, electrochemical, capacitive, FETs, resistive, microscopy, and ultrasound) for monitoring physical, chemical, and biological parameters that can improve the bioprocess control in cultured meat. The methods, operating principle, merits/demerits, and the main open challenges are reviewed with the aim to support the readers in advancing knowledge on novel sensing systems for cultured meat applications.

Intra-articular temperature monitoring during radiofrequency ablation in ex-vivo bovine hip joints via Fiber Bragg grating sensors.

PURPOSE: Radiofrequency ablation is an increasingly used surgical option for ablation, resection and coagulation of soft tissues in joint arthroscopy. One of the major issues of thermal ablation is the temperature monitoring across the target areas, as cellular mortality is a direct consequence of thermal dosimetry. Temperatures from 45 °C to 50 °C are at risk of damage to chondrocytes. One of the most reliable tools for temperature monitoring is represented by fiber optic sensors, as they allow accurate and real-time temperature measurement via a minimally invasive approach. The aim of this study was to determine, by fiber Bragg grating sensors (FBGs), the safety of radiofrequency ablation in tissue heating applied to ex-vivo bovine hip joints. METHODS: Ex vivo bovine hips were subjected to radiofrequency ablation, specifically in the acetabular labrum, for a total of two experiments. The WEREWOLF System (Smith + Nephew, Watford, UK) was employed in high operating mode and in a controlled ablation way. One optical fiber embedding seven FBGs was used to record multipoint temperature variations. Each sensor was 1 mm in length with a distance from edge to edge with each other of 2 mm. RESULTS: The maximum variation was recorded in both the tests by the FBG1 (i.e., the closest one to the electrode tip) and was lower than to 2.8 °C. The other sensors (from FBG2 to FBG7) did not record a significant temperature change throughout the duration of the experiment (maximum up to 0.7 °C for FBG7). CONCLUSIONS: No significant increase in temperature was observed at any of the seven sites. The sensor nearest to the radiofrequency source exhibited the highest temperature rise, but the variation was only 3 °C. The minimal temperature increase registered at the measurement sites, according to existing literature, is not expected to be cytotoxic. FBGs demonstrate the potential to fulfil the strict requirements for temperature measurements during arthroscopic surgery.

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.

Instrumented treadmill for run biomechanics analysis: a comparative study.

This study aims compare the spatiotemporal and kinematic running parameters obtained by the WalkerView (Tecnobody, Bergamo, Italy) with those recorded by a optoelectronic 3D motion capture system. Seventeen participants were simultaneously recorded by the WalkerView and a motion capture system during running tests on the WalkerView at two different speeds (i.e., 8 km/h and 10 km/h). Per each parameter and speed the Root Mean Square Error (RMSE), the intraclass correlation coefficient (ICC), and the mean of the difference (MOD) and limits of agreement (LOAs) indexes obtained from Bland-Altman analysis were used to compare the two systems. ICCs show an excellent agreement for the mean step time and the cadence at both testing speeds (ICC=0.993 at 8 km/h; ICC=0.998 at 10 km/h); a lower agreement was found for all the kinematic variables. Small differences for some spatio-temporal parameters and greater differences for the kinematic variables were found. Therefore, WalkerView could represent a practical, accessible, and less expensive tool for clinicians, researchers, and sports trainers to assess the characteristics spatio-temporal parameters of running in non-laboratory settings.

Respiratory Rate Estimation during Walking and Running Using Breathing Sounds Recorded with a Microphone.

Emerging evidence suggests that respiratory frequency (fR) is a valid marker of physical effort. This has stimulated interest in developing devices that allow athletes and exercise practitioners to monitor this vital sign. The numerous technical challenges posed by breathing monitoring in sporting scenarios (e.g., motion artifacts) require careful consideration of the variety of sensors potentially suitable for this purpose. Despite being less prone to motion artifacts than other sensors (e.g., strain sensors), microphone sensors have received limited attention so far. This paper proposes the use of a microphone embedded in a facemask for estimating fR from breath sounds during walking and running. fR was estimated in the time domain as the time elapsed between consecutive exhalation events retrieved from breathing sounds every 30 s. Data were collected from ten healthy subjects (both males and females) at rest and during walking (at 3 km/h and 6 km/h) and running (at 9 km/h and 12 km/h) activities. The reference respiratory signal was recorded with an orifice flowmeter. The mean absolute error (MAE), the mean of differences (MOD), and the limits of agreements (LOAs) were computed separately for each condition. Relatively good agreement was found between the proposed system and the reference system, with MAE and MOD values increasing with the increase in exercise intensity and ambient noise up to a maximum of 3.8 bpm (breaths per minute) and -2.0 bpm, respectively, during running at 12 km/h. When considering all the conditions together, we found an MAE of 1.7 bpm and an MOD ± LOAs of -0.24 ± 5.07 bpm. These findings suggest that microphone sensors can be considered among the suitable options for estimating fR during exercise.

Waveform Similarity Analysis Using Graph Mining for the Optimization of Sensor Positioning in Wearable Seismocardiography.

OBJECTIVE: A major concern with wearable devices aiming to measure the seismocardiogram (SCG) signal is the variability of SCG waveform with the sensor position and a lack of a standard measurement procedure. We propose a method to optimize sensor positioning based on the similarity among waveforms collected through repeated measurements. METHOD: we design a graph-theoretical model to evaluate the similarity of SCG signals and apply the proposed methodology to signals collected by sensors placed in different positions on the chest. A similarity score returns the optimal measurement position based on the repeatability of SCG waveforms. We tested the methodology on signals collected by using two wearable patches based on optical technology placed in two positions: mitral and aortic valve auscultation site (inter-position analysis). 11 healthy subjects were enrolled in this study. Moreover, we evaluated the influence of the subject's posture on waveform similarity with a view on ambulatory use (inter-posture analysis). RESULTS: the highest similarity among SCG waveforms is obtained with the sensor on the mitral valve and the subject lying down. CONCLUSIONS: our approach aims to be a step forward in the optimization of sensor positioning in the field of wearable seismocardiography. We demonstrate that the proposed algorithm is an effective method to estimate similarity among waveforms and outperforms the state-of-the-art in comparing SCG measurement sites. SIGNIFICANCE: results obtained from this study can be exploited to design more efficient protocols for SCG recording in both research studies and future clinical examinations.

Assessment of a Multi-Sensor FBG-Based Wearable System in Sitting Postures Recognition and Respiratory Rate Evaluation of Office Workers.

Due to prolonged incorrect sitting posture, upper body musculoskeletal disorders (UBMDs) are largely widespread among sedentary workers. Monitoring employees' sitting behaviors could be of great help in minimizing UBMDs' occurrence. In addition, being primarily influenced by psycho-physical stress conditions, respiratory rate (RR) would be a further useful parameter to delineate the workers' state of health. Wearable systems have emerged as a viable option for sitting posture and RR monitoring since enable continuous data collecting with no posture disturbances. Nevertheless, the main limits are poor fit, cumbersomeness, and movement restriction resulting in discomfort for the user. In addition, only few wearable solutions can track both these parameters contextually. To address these problems, in this study a flexible wearable system composed of seven modular sensing elements based on fiber Bragg grating (FBG) technology and designed to be worn on the back has been proposed to recognize the most common sitting postures (i.e., kyphotic, upright and lordotic) and estimate RR. The assessment was performed on ten volunteers showing good performances in postures recognition via Naïve Bayes classificator (accuracy >96.9%) and agreement with the benchmark in RR estimation (MAPE ranging between 0.74% and 3.83%, MODs close to zero, and LOAs between 0.76 bpm and 3.63 bpm). The method was then successfully tested on three additional subjects under different breathing conditions. The wearable system could offer great support for a better understanding of the workers' posture attitudes and contribute to gathering RR information to depict an overall picture of the users' state of health.

Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise.

Given the importance of respiratory frequency (fR) as a valid marker of physical effort, there is a growing interest in developing wearable devices measuring fR in applied exercise settings. Biosensors measuring chest wall movements are attracting attention as they can be integrated into textiles, but their susceptibility to motion artefacts may limit their use in some sporting activities. Hence, there is a need to exploit sensors with signals minimally affected by motion artefacts. We present the design and testing of a smart facemask embedding a temperature biosensor for fR monitoring during cycling exercise. After laboratory bench tests, the proposed solution was tested on cyclists during a ramp incremental frequency test (RIFT) and high-intensity interval training (HIIT), both indoors and outdoors. A reference flowmeter was used to validate the fR extracted from the temperature respiratory signal. The smart facemask showed good performance, both at a breath-by-breath level (MAPE = 2.56% and 1.64% during RIFT and HIIT, respectively) and on 30 s average fR values (MAPE = 0.37% and 0.23% during RIFT and HIIT, respectively). Both accuracy and precision (MOD ± LOAs) were generally superior to those of other devices validated during exercise. These findings have important implications for exercise testing and management in different populations.

Linear and Non-Linear Heart Rate Variability Indexes from Heart-Induced Mechanical Signals Recorded with a Skin-Interfaced IMU.

Heart rate variability (HRV) indexes are becoming useful in various applications, from better diagnosis and prevention of diseases to predicting stress levels. Typically, HRV indexes are retrieved from the heart's electrical activity collected with an electrocardiographic signal (ECG). Heart-induced mechanical signals recorded from the body's surface can be utilized to record the mechanical activity of the heart and, in turn, extract HRV indexes from interbeat intervals (IBIs). Among others, accelerometers and gyroscopes can be used to register IBIs from precordial accelerations and chest wall angular velocities. However, unlike electrical signals, the morphology of mechanical ones is strongly affected by body posture. In this paper, we investigated the feasibility of estimating the most common linear and non-linear HRV indexes from accelerometer and gyroscope data collected with a wearable skin-interfaced Inertial Measurement Unit (IMU) positioned at the xiphoid level. Data were collected from 21 healthy volunteers assuming two common postures (i.e., seated and lying). Results show that using the gyroscope signal in the lying posture allows accurate results in estimating IBIs, thus allowing extracting of linear and non-linear HRV parameters that are not statistically significantly different from those extracted from reference ECG.

Plant-Wear: A Multi-Sensor Plant Wearable Platform for Growth and Microclimate Monitoring.

Wearable devices are widely spreading in various scenarios for monitoring different parameters related to human and recently plant health. In the context of precision agriculture, wearables have proven to be a valuable alternative to traditional measurement methods for quantitatively monitoring plant development. This study proposed a multi-sensor wearable platform for monitoring the growth of plant organs (i.e., stem and fruit) and microclimate (i.e., environmental temperature-T and relative humidity-RH). The platform consists of a custom flexible strain sensor for monitoring growth when mounted on a plant and a commercial sensing unit for monitoring T and RH values of the plant surrounding. A different shape was conferred to the strain sensor according to the plant organs to be engineered. A dumbbell shape was chosen for the stem while a ring shape for the fruit. A metrological characterization was carried out to investigate the strain sensitivity of the proposed flexible sensors and then preliminary tests were performed in both indoor and outdoor scenarios to assess the platform performance. The promising results suggest that the proposed system can be considered one of the first attempts to design wearable and portable systems tailored to the specific plant organ with the potential to be used for future applications in the coming era of digital farms and precision agriculture.

Current understanding, challenges and perspective on portable systems applied to plant monitoring and precision agriculture.

The devastating effects of global climate change on crop production and exponential population growth pose a major challenge to agricultural yields. To cope with this problem, crop performance monitoring is becoming increasingly necessary. In this scenario, the use of sensors and biosensors capable of detecting changes in plant fitness and predicting the evolution of their morphology and physiology has proven to be a useful strategy to increase crop yields. Flexible sensors and nanomaterials have inspired the emerging fields of wearable and on-plant portable devices that provide continuous and accurate long-term sensing of morphological, physiological, biochemical, and environmental parameters. This review provides an overview of novel plant sensing technologies by discussing wearable and integrated devices proposed for engineering plant and monitoring its morphological traits and physiological processes, as well as plant-environment interactions. For each application scenario, the state-of-the-art sensing solutions are grouped according to the plant organ on which they have been installed highlighting their main technological advantages and features. Finally, future opportunities, challenges and perspectives are discussed. We anticipate that the application of this technology in agriculture will provide more accurate measurements for farmers and plant scientists with the ability to track crop performance in real time. All of this information will be essential to enable rapid optimization of plants development through tailored treatments that improve overall plant health even under stressful conditions, with the ultimate goal of increasing crop productivity in a more sustainable manner.

Preliminary Assessment of a Flexible Multi-Sensor Wearable System Based on Fiber Bragg Gratings for Respiratory Monitoring of Hemiplegic Patients.

Respiratory diseases are common in post-stroke hemiplegic patients and represent a major social problem as they worsen the quality of life and reduce the life span. As a consequence, being able to monitor respiratory parameters such as the respiratory rate (RR) and assess the presence of respiratory asynchronies could be of paramount importance to define hemiplegics' health status. Moreover, RR is a useful parameter to investigate the level of fatigue and distress that these patients undergo during rehabilitation processes. Although motion capture systems and flowmeters are the leading instruments for respiratory pattern evaluation, smart wearable systems are gaining ever more acceptance since they allow continuous monitoring by detecting chest wall breathing displacements, ensuring reduced costs and no need for dedicated spaces. Among other sensing technologies, fiber Bragg grating (FBG) sensors have emerged thanks to their high sensitivity to strain, lightness, and multiplexing capability. In this work, a wearable system composed of four flexible dumbbell-shaped sensing modules is proposed for respiratory monitoring in hemiplegic patients. The system is light and easy to wear and can be adapted to any anthropometry thanks to the modular anchoring system. Its feasibility assessment in RR evaluation was performed on seven hemiplegic volunteers in eupnea and tachypnea breathing conditions. In addition, an explorative investigation was conducted to assess the system's ability to detect asynchronies between torso compartments. The good results suggest that this device could be a useful instrument to support clinicians and operators in hemiplegic patients' management.

Comparison between Chest-Worn Accelerometer and Gyroscope Performance for Heart Rate and Respiratory Rate Monitoring.

The demand for wearable devices to simultaneously monitor heart rate (HR) and respiratory rate (RR) values has grown due to the incidence increase in cardiovascular and respiratory diseases. The use of inertial measurement unit (IMU) sensors, embedding both accelerometers and gyroscopes, may ensure a non-intrusive and low-cost monitoring. While both accelerometers and gyroscopes have been assessed independently for both HR and RR monitoring, there lacks a comprehensive comparison between them when used simultaneously. In this study, we used both accelerometers and gyroscopes embedded in a single IMU sensor for the simultaneous monitoring of HR and RR. The following main findings emerged: (i) the accelerometer outperformed the gyroscope in terms of accuracy in both HR and RR estimation; (ii) the window length used to estimate HR and RR values influences the accuracy; and (iii) increasing the length over 25 s does not provide a relevant improvement, but accuracy improves when the subject is seated or lying down, and deteriorates in the standing posture. Our study provides a comprehensive comparison between two promising systems, highlighting their potentiality for real-time cardiorespiratory monitoring. Furthermore, we give new insights into the influence of window length and posture on the systems' performance, which can be useful to spread this approach in clinical settings.