Search Results (87)

Stroke is a significant global health concern characterized by the abrupt disruption of cerebral blood flow, leading to neurological impairment. Accurate and timely diagnosis—enabled by imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI)—is essential for differentiating stroke types and initiating interventions like thrombolysis, thrombectomy, or surgical management. In parallel, recent advancements in wearable technology, particularly smart clothing, offer new opportunities for stroke prevention, real-time monitoring, and rehabilitation. These garments integrate various sensors, including electrocardiogram (ECG) electrodes, electroencephalography (EEG) caps, electromyography (EMG) sensors, and motion or pressure sensors, to continuously track physiological and functional parameters. For example, ECG shirts monitor cardiac rhythm to detect atrial fibrillation, smart socks assess gait asymmetry for early mobility decline, and EEG caps provide data on neurocognitive recovery during rehabilitation. These technologies support personalized care across the stroke continuum, from early risk detection and acute event monitoring to long-term recovery. Integration with AI-driven analytics further enhances diagnostic accuracy and therapy optimization. This narrative review explores the application of smart clothing in conjunction with traditional imaging to improve stroke management and patient outcomes through a more proactive, connected, and patient-centered approach. Full article

Advancements in thermoregulating textiles have been propelled by innovations in nanotechnology, composite materials, and smart fiber engineering. This article reviews recent scholarly papers on experimental passive and active thermoregulating textiles to present the latest advancements in these fabrics, their mechanisms of thermoregulation, and their feasibility for use. The review underscores that phase-change materials enhanced with graphene, boron nitride, and carbon nanofibers offer superior thermal conductivity, phase stability, and flexibility, making them ideal for wearable applications. Shape-stabilized phase-change materials and aerogel-infused fibers have shown promising results in outdoor, industrial, and emergency settings due to their durability and high insulation efficiency. Radiative cooling textiles, engineered with hierarchical nanostructures and Janus wettability, demonstrate passive temperature regulation through selective solar reflection and infrared emission, achieving substantial cooling effects without external energy input. Thermo-responsive, shape-memory materials, and moisture-sensitive polymers enable dynamic insulation and actuation. Liquid-cooling garments and thermoelectric hybrids deliver precise temperature control but face challenges in portability and power consumption. While thermoregulating textiles show promise, the main challenges include achieving scalable manufacturing, ensuring material flexibility, and integrating multiple functions without sacrificing comfort. Future research should focus on hybrid systems combining passive and active mechanisms, user-centric wearability studies, and cost-effective fabrication methods. These innovations hold significant potential for applications in extreme environments, athletic wear, military uniforms, and smart clothing, contributing to energy efficiency, health, and comfort in a warming climate. Full article

Currently, the sedentary nature of office work has led to a steady increase in the prevalence of spinal disorders, including lower back pain, back pain, and neck pain. Medical research has shown that monitoring and improving sitting posture is an important measure to prevent spinal discomfort. The emergence and development of wearable technology have enabled more people to effectively monitor their health. In this study, we propose and design a textile sensor-based sitting posture correction smart garment to realize dynamic sitting reminders aimed at meeting the needs of sedentary office workers. The garment achieves real-time sitting posture recognition through integrated machine learning algorithms, with a recognition accuracy exceeding 95% using a random forest classifier. Additionally, we developed haptic vibration feedback and visual GUI feedback modes to provide sitting posture intervention and dynamic sitting reminders. To evaluate the system’s effectiveness and usability, we conducted comparative experiments analyzing sitting posture behavior before and after wearing the smart garment, along with a user satisfaction survey. The results demonstrate that the smart garment effectively helps office workers adjust their sitting posture and reduces the risk of spinal discomfort associated with prolonged sedentary work. Full article

Circus athletes represent a unique population of performers engaging in highly demanding physical activities, yet they remain underrepresented in scientific research. This paper aims to address this gap by exploring the challenges and making recommendations in applying biomechanics and exercise physiology instruments to understand circus athlete movements. Laboratory-based tools such as motion capture technology, force platforms, and metabolic carts offer valuable insights into movement patterns and physiological responses. The growth of wearable technology, including smart garments, inertial measurement units, and Global Positioning System (GPS) devices, has led to opportunities to gather data to quantify the dynamic movements characteristic of circus acts. This paper discusses the capabilities of these devices, emphasizing the importance of selecting appropriate technology tailored to the specific demands of circus performances. By understanding the biomechanics and physiological demands of various circus movements, researchers can develop targeted training and injury prevention programs, ultimately supporting the health and performance of circus athletes. This paper underscores the need for comprehensive, evidence-based strategies to ensure the well-being and success of these extraordinary performers. Full article

Nowadays, the emphasis on sustainable performance highlights the necessity for resilience and innovation in tackling environmental and economic concerns within supply chain operations. Therefore, this study investigates the impact of six supply chain management practices (SCMPs) on organizational performance (OP) and environmental sustainability performance (ESP), along with the moderating role of supply chain dynamism. This research was conducted within medium and large export manufacturing firms in Jordan’s Garment, Textile, and Leather (GTL) sector, a pivotal export industry critical to the country’s economy. Data were gathered from 204 managers, employing an online self-administered questionnaire, using a quantitative research approach. The hypotheses were examined via structural equation modeling (SEM) through the SmartPLS software4. The findings reveal that ESP was significantly influenced by strategic supplier partnership and postponement. Additionally, the level of information sharing and internal lean practices were found to have a dual impact on both OP and ESP. Supply chain dynamism acted as a significant moderator only in the relationship between postponement and both OP and ESP. This study fills a significant gap in the GTL context in developing economies for export manufacturing firms that contribute to the current literature. What makes it original is its consideration of supply chain dynamism as a moderating variable and its context in an important sector for Jordan’s economy. In conclusion, the results present valuable implications for practitioners on developing custom SCMPs for sustainable and operational performance objectives in the dynamic supply chain context. Future studies should adopt probability sampling methods to improve the generalizability of the findings. Further, the findings should be confirmed by conducting a study on other exporting sectors or geographical areas to gain additional perspectives on the relationships between SCMPs, OP, and ESP. Full article

In recent years, smart devices have proven their effectiveness in monitoring mental health issues and have played a crucial role in providing therapy. The ability to embed sensors in fabrics opens new horizons for mental healthcare, addressing the growing demand for innovative solutions in monitoring and therapy. The objective of this review is to understand mental health, its impact on the human body, and the latest advancements in the field of smart textiles (sensors, electrodes, and smart garments) for monitoring physiological signals such as respiration rate (RR), electroencephalogram (EEG), electrodermal activity (EDA), electrocardiogram (ECG), and cortisol, all of which are associated with mental health disorders. Databases such as Web of Science (WoS) and Scopus were used to identify studies that utilized smart textiles to monitor specific physiological parameters. Research indicates that smart textiles provide promising results compared to traditional methods, offering enhanced comfort for long-term monitoring. Full article

This study examines how environmental regulation (ER), green intellectual capital (GIC), green human resource management (GHRM), and green ambidextrous innovation (GAI) contribute to enhancing the sustainable performance (SP) of manufacturing firms. Using a quantitative approach, data from 472 managers of green garment manufacturing firms in Bangladesh were analyzed with SmartPLS4 software. The results indicate that GHRM and GIC positively impact SP, with GIC exerting a stronger influence on GAI—encompassing green exploitative innovation (EIGI) and green exploratory innovation (ERGI)—compared to GHRM. Additionally, GAI positively affects SP and serves as a partial mediator in the GIC-SP relationship but not in the GHRM-SP relationship. ER negatively moderates the GHRM-SP and GHRM-GAI links, while it positively moderates the GIC-GAI relationship, albeit weakly in the GIC-SP connection. This study highlights GAI’s mediating roles in the GHRM-SP (specifically, GHRM-EIGI-SP and GHRM-ERGI-SP) and GIC-SP (specifically, GIC-EIGI-SP and GIC-ERGI-SP) relationships within a regulatory context. By introducing fresh perspectives, this research advances green management studies, offering valuable insights for academics and industry professionals. It provides a strategic framework for firms to navigate regulations, foster innovation, optimize human and intangible resources, and enhance sustainable performance, thereby positioning themselves as leaders in the global market. Full article

Freezing of gait (FOG) is a disabling yet poorly understood paroxysmal gait disorder affecting the vast majority of patients with Parkinson’s disease (PD) as they reach advanced stages of the disorder. Falling is one of the most disabling consequences of a FOG episode; it often results in injury and a future fear of falling, leading to diminished social engagement, a reduction in general fitness, loss of independence, and degradation of overall quality of life. Currently, there is no robust or reliable treatment against FOG in PD. In the absence of reliable and effective treatment for Parkinson’s disease, alleviating the consequences of FOG represents an unmet clinical need, with the first step being reliable FOG prediction. Current methods for FOG prediction and prevention cannot provide real-time readouts and are not sensitive enough to detect changes in walking patterns or balance. To fill this gap, we developed an sEMG system consisting of a soft, wearable garment (pair of shorts and two calf sleeves) embedded with screen-printed electrodes and stretchable traces capable of picking up and recording the electromyography activities from lower limb muscles. Here, we report on the testing of these garments in healthy individuals and in patients with PD FOG. The preliminary testing produced an initial time-to-onset commencement that persisted > 3 s across all patients, resulting in a nearly 3-fold drop in sEMG activity. We believe that these initial studies serve as a solid foundation for further development of smart digital textiles with integrated bio and chemical sensors that will provide AI-enabled, medically oriented data. Full article

The position that a woman adopts during breastfeeding is important for both infant and maternal health; however, many women experience musculoskeletal pain due to poor posture during breastfeeding, which is a known factor in low exclusive breastfeeding rates. Posture monitoring is an effective intervention, but existing wearable devices do not consider the ergonomics of nursing mothers and breastfeeding scenarios. In this study, nursing underwear was developed with posture monitoring and a real-time feedback system using accelerometers and flexible bending sensors targeting the neck and upper thoracic spine. Semi-structured interviews were conducted with 12 Chinese mothers to identify key challenges and inform the design. After designing and producing the prototype, wear trials were conducted with two participants who tested both the prototype and a commercial sample while holding a 4 kg baby doll. Video recordings and questionnaires were used to assess the underwear’s effectiveness. The results showed improvements in postural alignment and an increase in the frequency and duration of relaxation periods. Participants reported that the prototype surpassed the commercial sample in functionality, comfort, and aesthetics. These findings are significant for postpartum health and provide guidelines for future smart nursing garment development. Full article

Physical therapy is often essential for complete recovery after injury. However, a significant population of patients fail to adhere to prescribed exercise regimens. Lack of motivation and inconsistent in-person visits to physical therapy are major contributing factors to suboptimal exercise adherence, slowing the recovery process. With the advancement of virtual reality (VR), researchers have developed remote virtual rehabilitation systems with sensors such as inertial measurement units. A functional garment with an integrated wearable sensor can also be used for real-time sensory feedback in VR-based therapeutic exercise and offers affordable remote rehabilitation to patients. Sensors integrated into wearable garments offer the potential for a quantitative range of motion measurements during VR rehabilitation. In this research, we developed and validated a carbon nanocomposite-coated knit fabric-based sensor worn on a compression sleeve that can be integrated with upper-extremity virtual rehabilitation systems. The sensor was created by coating a commercially available weft knitted fabric consisting of polyester, nylon, and elastane fibers. A thin carbon nanotube composite coating applied to the fibers makes the fabric electrically conductive and functions as a piezoresistive sensor. The nanocomposite sensor, which is soft to the touch and breathable, demonstrated high sensitivity to stretching deformations, with an average gauge factor of ~35 in the warp direction of the fabric sensor. Multiple tests are performed with a Kinarm end point robot to validate the sensor for repeatable response with a change in elbow joint angle. A task was also created in a VR environment and replicated by the Kinarm. The wearable sensor can measure the change in elbow angle with more than 90% accuracy while performing these tasks, and the sensor shows a proportional resistance change with varying joint angles while performing different exercises. The potential use of wearable sensors in at-home virtual therapy/exercise was demonstrated using a Meta Quest 2 VR system with a virtual exercise program to show the potential for at-home measurements. Full article

Continuous monitoring of lower extremity muscles is necessary, as the muscles support many human daily activities, such as maintaining balance, standing, walking, running, and jumping. However, conventional electromyography and physiological cross-sectional area methods inherently encounter obstacles when acquiring precise and real-time data pertaining to human bodies, with a notable lack of consideration for user comfort. Benefitting from the fast development of various fabric-based sensors, this paper addresses these current issues by designing an integrated smart compression stocking system, which includes compression garments, fabric-embedded capacitive pressure sensors, an edge control unit, a user mobile application, and cloud backend. The pipeline architecture design and component selection are discussed in detail to illustrate a comprehensive user-centered STIMES design. Twelve healthy young individuals were recruited for clinical experiments to perform maximum voluntary isometric ankle plantarflexion contractions. All data were simultaneously collected through the integrated smart compression stocking system and a muscle force measurement system (Humac NORM, software version HUMAC2015). The obtained correlation coefficients above 0.92 indicated high linear relationships between the muscle torque and the proposed system readout. Two-way ANOVA analysis further stressed that different ankle angles (p = 0.055) had more important effects on the results than different subjects (p = 0.290). Hence, the integrated smart compression stocking system can be used to monitor the muscle force of the lower extremities in isometric mode. Full article

Electronic textiles (e-textiles) are a branch of wearable technology based on integrating smart systems into textile materials creating different possibilities, transforming industries, and improving individuals’ quality of life. E-textiles hold vast potential, particularly for use in personal protective equipment (PPE) by embedding sensors and smart technologies into garments, thus significantly enhancing safety and performance. Although this branch of research has been active for several decades now, only a few products have made it to the market. Achieving durability, reliability, user acceptance, sustainability, and integration into current manufacturing processes remains challenging. High levels of reliability and user acceptance are critical for technical textiles, such as those used in PPE. While studies address washing reliability and field tests, they often overlook end user preferences regarding smart textiles. This paper presents a narrow fabric-based e-textile system co-developed by engineers, garment and textiles’ manufacturers, and firefighters. It highlights material choices and integration methods, and evaluates the system’s reliability, sustainability, and user experience, providing comprehensive insights into developing and analyzing e-textile products, particularly in the PPE field. Full article

Textile-based wearable robotics increasingly integrates sensing and energy materials to enhance functionality, particularly in physiological monitoring, demanding higher-performing and abundant robotic textiles. Among the alternatives, activated carbon cloth stands out due to its monolithic nature and high specific surface area, enabling uninterrupted electron transfer and energy storage capability in the electrical double layer, respectively. Yet, the potential of monolithic activated carbon cloth electrodes (MACCEs) in wearables still needs to be explored, particularly in sensing and energy storage. MACCE conductance increased by 29% when saturated with Na₂SO₄ aqueous electrolyte and charged from 0 to 0.375 V. MACCE was validated for measuring pressure up to 28 kPa at all assessed charge levels. Electrode sensitivity to compression decreased by 30% at the highest potential due to repulsive forces between like charges in electrical double layers at the MACCE surface, counteracting compression. MACCE’s controllable sensitivity decrease can be beneficial for garments in avoiding irrelevant signals and focusing on essential health changes. A MACCE charge-dependent sensitivity provides a method for assessing local electrode charge. Our study highlights controlled charging and electrolyte interactions in MACCE for multifunctional roles, including energy transmission and pressure detection, in smart wearables. Full article

Textile-based sensors have a broad application potential in technical textiles, e.g., for measuring temperature, strain, humidity, pressure, etc. Moreover, textile-based sensors represent a promising class of sensor technologies that open up new possibilities for applications in health monitoring, sports, wearables, and smart clothing by integrating sensor technology into textiles. These sensors utilize flexible and stretchable materials to enable their seamless integration into garments, allowing them to be worn comfortably and unobtrusively. Their appeal lies in their breathability, stretchability, flexibility, and comfortable feel, along with an easier fabrication process compared to traditional rigid sensors. The growing importance of flexible, thin, and lightweight sensors in electronic wearables is increasingly being researched, which is reflected in the growing number of publications. By using different fibres and coatings, textile-based sensors can detect a variety of physiological parameters such as heart rate, respiratory rate, muscle activity, and posture. In general, the integration of textile-based sensors into technical textiles allows for the creation of intelligent and functional materials that offer a wide range of applications. This incorporation is critical for the functionality of products, enabling them to sense, respond, and adapt to external stimuli. The evergrowing demand for smart textiles creates an increase in expectations for the range, accuracy, and stability of sensor measurements. The properties of both the textile and conductive components, alongside the level of mechanical impact that they are subjected to during use, significantly influence the overall reliability and durability of the electronic textiles. So far, only few solutions have passed durability tests, which has resulted in products that appear promising for marketable product solutions. This article gives an overview of the current research on textile-based sensors for various applications in technical textiles and smart clothing, as well as the materials and fabrication techniques used. Furthermore, it addresses challenges in sensor performance and future advancements in materials and technologies. Full article

Respiratory rate ($f_R$) 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 $f_R$ 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$\mathsf{\Omega }\cdot {\%}^{-1}$ and 9.1$\mathsf{\Omega }\cdot {\%}^{-1}$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. Full article