Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview

A quantitative evaluation of kinetic parameters, the joint’s range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device’s positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user’s vital signs directly from the body in an accurate and non–invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach’s subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post–operative rehabilitation and athletes’ training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user’s health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties

Proceedings XXI Congresso SIAMOC 2021

XXI Congresso Annuale della SIAMOC, modalità telematica il 30 settembre e il 1° ottobre 2021. Come da tradizione, il congresso vuole essere un’occasione di arricchimento e mutuo scambio, dal punto di vista scientifico e umano. Verranno toccati i temi classici dell’analisi del movimento, come lo sviluppo e l’applicazione di metodi per lo studio del movimento nel contesto clinico, e temi invece estremamente attuali, come la teleriabilitazione e il telemonitoraggio

Applications of EMG in Clinical and Sports Medicine

This second of two volumes on EMG (Electromyography) covers a wide range of clinical applications, as a complement to the methods discussed in volume 1. Topics range from gait and vibration analysis, through posture and falls prevention, to biofeedback in the treatment of neurologic swallowing impairment. The volume includes sections on back care, sports and performance medicine, gynecology/urology and orofacial function. Authors describe the procedures for their experimental studies with detailed and clear illustrations and references to the literature. The limitations of SEMG measures and methods for careful analysis are discussed. This broad compilation of articles discussing the use of EMG in both clinical and research applications demonstrates the utility of the method as a tool in a wide variety of disciplines and clinical fields

Proceedings SIAMOC 2019

Il congresso annuale della Società Italiana di Analisi del Movimento in Clinica, giunto quest'anno alla sua ventesima edizione, ritorna a Bologna, che già ospitò il terzo congresso nazionale nel 2002. Il legame tra Bologna e l'analisi del movimento è forte e radicato, e trova ampia linfa sia nel contesto accademico che nel ricco panorama di centri clinici d'eccellenza. Il congresso SIAMOC, come ogni anno, è l’occasione per tutti i professionisti dell’ambito clinico, metodologico ed industriale di incontrarsi, presentare le proprie ricerche e rimanere aggiornati sulle più recenti innovazioni nell’ambito dell’applicazione clinica dei metodi di analisi del movimento. Questo ha contribuito, in questi venti anni, a fare avanzare sensibilmente la ricerca italiana nel settore, conferendole un respiro ed un impatto internazionale, e a diffonderne l'applicazione clinica per migliorare la valutazione dei disordini motori, aumentare l'efficacia dei trattamenti attraverso l'analisi quantitativa dei dati e una più focalizzata pianificazione dei trattamenti, ed inoltre per quantificare i risultati delle terapie correnti

Proceedings SIAMOC 2019

Il congresso annuale della Società Italiana di Analisi del Movimento in Clinica, giunto quest'anno alla sua ventesima edizione, ritorna a Bologna, che già ospitò il terzo congresso nazionale nel 2002. Il legame tra Bologna e l'analisi del movimento è forte e radicato, e trova ampia linfa sia nel contesto accademico che nel ricco panorama di centri clinici d'eccellenza. Il congresso SIAMOC, come ogni anno, è l’occasione per tutti i professionisti dell’ambito clinico, metodologico ed industriale di incontrarsi, presentare le proprie ricerche e rimanere aggiornati sulle più recenti innovazioni nell’ambito dell’applicazione clinica dei metodi di analisi del movimento. Questo ha contribuito, in questi venti anni, a fare avanzare sensibilmente la ricerca italiana nel settore, conferendole un respiro ed un impatto internazionale, e a diffonderne l'applicazione clinica per migliorare la valutazione dei disordini motori, aumentare l'efficacia dei trattamenti attraverso l'analisi quantitativa dei dati e una più focalizzata pianificazione dei trattamenti, ed inoltre per quantificare i risultati delle terapie correnti

Towards Remote Gait Analysis: Combining Physics and Probabilistic Models for Estimating Human Joint Mechanics

The connected health movement and remote patient monitoring promise to revolutionize patient care in multiple clinical contexts. In orthopedics, continuous monitoring of human joint and muscle tissue loading in free-living conditions will enable novel insight concerning musculoskeletal disease etiology. These developments are necessary for comprehensive patient characterization, progression monitoring, and personalized therapy. This vision has motivated many recent advances in wearable sensor-based algorithm development that aim to perform biomechanical analyses traditionally restricted to confined laboratory spaces. However, these techniques have not translated to practical deployment for remote monitoring. Several barriers to translation have been identified including complex sensor arrays. Thus, the aim of this work was to lay the foundation for remote gait analysis and techniques for estimating clinically relevant biomechanics with a reduced sensor array. The first step in this process was to develop an open-source platform that generalized the processing pipeline for automated remote biomechanical analysis. The clinical utility of the platform was demonstrated for monitoring patient gait following knee surgery using continuous recordings of thighworn accelerometer data and rectus femoris electromyograms (EMG) during free-living conditions. Individual walking bouts were identified from which strides were extracted and characterized for patient evaluation. A novel, multifactorial asymmetry index was proposed based on temporal, EMG, and kinematic descriptors of gait that was able to differentiate between patients at different stages of recovery and that was more sensitive to recovery time than were indices of cumulative physical activity. The remainder of the work focused on algorithms for estimating joint moment and simulating muscle contraction dynamics using a reduced sensor array. A hybrid technique was proposed that combined both physics and probabilistic models in a complementary fashion. Specifically, the notion of a muscle synergy function was introduced that describes the mapping between excitations from a subset of muscles and excitations from other synergistic muscles. A novel model of these synergy functions was developed that enabled estimation of unmeasured muscle excitations using a measured subset. Data from thigh- and shank-worn inertial sensors were used to estimate segment kinematics and muscle-tendon unit (MTU) lengths using physics-based techniques and a model of the musculoskeletal geometry. These estimates of muscle excitation and MTU length were used as inputs for EMG-driven simulation of muscle contraction. Estimates of muscle force, power, and work as well as net joint moment from the proposed hybrid technique were compared to estimates from laboratory-based techniques. This presents the first sensor-only (four EMG and two inertial sensors) simulation of muscle contraction dynamics and joint moment estimation using machine learning only for estimating unmeasured muscle excitations. This work provides the basis for automated remote biomechanical analysis with reduced sensor arrays; from raw sensor recordings to estimates of muscle moment, force, and power. The proposed hybrid technique requires data from only four EMG and two inertial sensors and work has begun to seamlessly integrate these sensors into a knee brace for monitoring patients following knee surgery. Future work should build on these developments including further validation and design of methods utilizing remotely and longitudinally observed biomechanics for prognosis and optimizing patient-specific interventions

Proceedings XXII Congresso SIAMOC 2022

Il congresso annuale della Società Italiana di Analisi del Movimento in Clinica dà l’occasione a tutti i professionisti, dell’ambito clinico e ingegneristico, di incontrarsi, presentare le proprie ricerche e rimanere aggiornati sulle più recenti innovazioni nell’ambito dell’applicazione clinica dei metodi di analisi del movimento, al fine di promuoverne lo studio e le applicazioni cliniche per migliorare la valutazione dei disordini motori, aumentare l’efficacia dei trattamenti attraverso l’analisi quantitativa dei dati e una più focalizzata pianificazione dei trattamenti, ed inoltre per quantificare i risultati delle terapie correnti

Home-based rehabilitation of the shoulder using auxiliary systems and artificial intelligence: an overview

Advancements in modern medicine have bolstered the usage of home-based rehabilitation services for patients, particularly those recovering from diseases or conditions that necessitate a structured rehabilitation process. Understanding the technological factors that can influence the efficacy of home-based rehabilitation is crucial for optimizing patient outcomes. As technologies continue to evolve rapidly, it is imperative to document the current state of the art and elucidate the key features of the hardware and software employed in these rehabilitation systems. This narrative review aims to provide a summary of the modern technological trends and advancements in home-based shoulder rehabilitation scenarios. It specifically focuses on wearable devices, robots, exoskeletons, machine learning, virtual and augmented reality, and serious games. Through an in-depth analysis of existing literature and research, this review presents the state of the art in home-based rehabilitation systems, highlighting their strengths and limitations. Furthermore, this review proposes hypotheses and potential directions for future upgrades and enhancements in these technologies. By exploring the integration of these technologies into home-based rehabilitation, this review aims to shed light on the current landscape and offer insights into the future possibilities for improving patient outcomes and optimizing the effectiveness of home-based rehabilitation programs.info:eu-repo/semantics/publishedVersio

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level

Gait impairment in cervical spondylotic myelopathy: Analysis, impact on function, and effect of surgical intervention

Chest pain is one of the most frequent complaints in medical settings, yet more than half of cases have no detectable cause. Once a cardiac cause has been excluded, patients are typically discharged with a label of non-cardiac chest pain (NCCP). Patients with NCCP have been shown to have poor outcomes in terms of continued symptoms, distress, and continuing concern about heart disease. In addition, NCCP represents a significant burden to health services. The aetiology and management of NCCP is under-researched and poorly understood. This study sought to examine the predictors of persistent pain and health service use for patients in whom a cardiac diagnosis had been excluded. It also sought to explore how patients interpreted their symptoms in the context of normal test results, and the impact of their experiences with health services on these interpretations. A mixed-methods design was adopted. A prospective cohort study was initially conducted with 145 participants with chest pain who attended exercise stress testing and had normal test results. At one-year follow-up, 69% reported continued pain. In addition, nearly half of participants had returned to their general practitioner and one in ten had attended the emergency department for the investigation of chest pain. In logistic regression analyses, the variables heartburn, pain precipitated by movement, cardiac anxiety, illness perceptions, and lack of communication about test results were predictive of persistent chest pain. When participants with continued chest pain were categorised into persistent healthcare users and non-persistent healthcare users, these variables were predominantly associated with participants with persistent health service use for chest pain. In addition, a number of psychological variables including anxiety and depression distinguished the persistent service users. Employment appeared to be a protective factor against persistent pain and related service use. A small sample of participants from this cohort was interviewed in a qualitative study informed by the principles of Interpretative Phenomenological Analysis (IPA). Analysis revealed three predominant themes: 1) the disempowerment of normal test results; 2) limbo - the inner struggle of negating and relating to potential causes; and 3) the inadequacy of healthcare to validate and care for symptoms. The dynamic, complex process of interpreting symptoms and deciding whether to seek healthcare was illuminated. The results indicate that interventions targeting the assessment of a potential gastro-oesophageal or musculoskeletal cause and the reduction of cardiac anxiety are likely to improve outcomes in these patients. Improved communication with patients is also indicated. Psychological factors appear to drive persistent service use and interventions targeting these are likely to reduce medical costs. Patients with NCCP are not a homogenous patient group and an individualised, stepped-care approach to management appears to be warranted