Methods and good practice guidelines for human joint kinematics estimation through magnetic and inertial wearable sensors

According to the World Health Organization, the ability to move is recognized as a key factor for the human well-being. From the wearable Magnetic and Inertial Measurement Units (MIMUs) signals it is possible to extract several digital mobility outcomes including the joint kinematics. To this end, it is first required to estimate the orientation of the MIMUs by means of a sensor fusion algorithm (SFA). After that, the relative orientation is computed and then decomposed to obtain the joint angles. However, the MIMUs do not provide a direct output of the physical quantity of interest which can be only determined after an ad hoc processing of their signals. It follows that the joint angle accuracy mostly depends on multiple factors. The first one is the magnitude of the MIMU measurements errors and up to date there is still a lack of methods for their characterization. A second crucial factor is the choice of the SFA to use. Despite the abundance of formulations in the literature, no-well established conclusions about their accuracy have been reached yet. The last factor is the biomechanical model used to compute the joint angles. In this context, unconstrained methods offer a simple way to decompose the relative orientation using the Euler angles but suffer from the inherent issues related to the SFA. In contrast, constrained approaches aim at increasing the robustness of the estimates by adopting models in which an objective function is minimized through the definition of physiological constraints. This thesis proposed the methods to accurately estimate the human joint kinematics starting from the MIMU signals. Three main contributions were provided. The first consisted in the design of a comprehensive battery of tests to completely characterize the sources of errors affecting the quality of the measurements. These tests rely on simple hypotheses based on the sensor working principles and do not require expensive equipment. Nine parameters were defined to quantify the signal accuracy improvements (if any) of 24 MIMUs before and after the refinement of their calibration coefficients. The second contribution was focused on the SFAs. Ten among the most popular SFAs were compared under different experimental conditions including different MIMU models and rotation rate magnitudes. To perform a “fair” comparison it was necessary to set the optimal parameter values for each SFA. The most important finding was that all the errors fall within a range from 3.8 deg to 7.1 deg thus making it impossible to draw any conclusions about the best performing SFA since no statistically significant differences were found. In addition, the orientation accuracy was heavily influenced by the experimental variables. After that, a novel method was designed to estimate the suboptimal parameter values of a given SFA without relying on any orientation reference. The maximum difference between the errors obtained using optimal and suboptimal parameter values amounted to 3.7 deg and to 0.6 deg on average. The last contribution consisted in the design of an unconstrained and a constrained methods for estimating the joint kinematics without considering the magnetometer to avoid the ferromagnetic disturbances. The unconstrained method was employed in a telerehabilitation platform in which the joint angles were estimated in real time. Errors collected during the execution of a full-body protocol were lower than 5 deg (considered the acceptability threshold). However, this method may be inaccurate after few minutes since no solutions can be taken to mitigate the drift error. To overcome this limitation a constrained method was developed based on a robotic model of the upper limb to set appropriate constraints. Errors relative to a continuous robot motion for twenty minutes were lower than 3 deg at most suggesting the feasibility of employing these solutions in the rehabilitation programs to properly plan the treatment and to accurately evaluate the outcomes

Development and implementation of technologies for physical telerehabilitation in Latin America:

La telerehabilitation ha surgido debido a la inclusión de tecnologías emergentes para la captura, transmisión, análisis y visualización de patrones de movimiento asociados a pacientes con trastornos músculo-esqueléticos. Esta estrategia permite llevar a cabo procesos de diagnóstico y tratamientos de rehabilitación a distancia. Este artículo presenta una revisión sistemática del desarrollo e implementación actual de las tecnologías de telerehabilitación en la región latinoamericana. El objetivo principal es explorar, a partir de la literatura científica reportada y fuentes divulgativas, si las tecnologías de telerehabilitación han logrado ser introducidas en esta región. Asimismo, este trabajo revela los prototipos actuales o sistemas que están en desarrollo o que ya están siendo usados. Se llevó a cabo una revisión sistemática, mediante dos búsquedas diferentes. La primera implicó una búsqueda bibliográfica rigurosa en los repositorios digitales científicos más relevantes en el área y la segunda incluyó proyectos y programas de telerehabilitación implementados en la región, encontrados a partir de una búsqueda avanzada en Google. Se encontró un total de 53 documentos de seis países (Colombia, Brasil, México, Ecuador, Chile y Argentina); la mayoría de ellos estaban enfocados en iniciativas académicas y de investigación para el desarrollo de prototipos tecnológicos para telerehabilitación de pacientes pediátricos y adultos mayores, afectados por deficiencias motoras o funcionales, parálisis cerebral, enfermedades neurocognitivas y accidente cerebrovascular. El análisis de estos documentos reveló la necesidad de un extenso enfoque integrado de salud y sistema social para aumentar la disponibilidad actual de iniciativas de telerehabilitación en la región latinoamericana.Telerehabilitation has arised by the inclusion of emerging technologies for capturing, transmitting, analyzing and visualizing movement patterns associated to musculoskeletal disorders. This therapeutic strategy enables to carry out diagnosis processes and provide rehabilitation treatments. This paper presents a systematic review of the current development and implementation of telerehabilitation technologies in Latin America. The main goal is to explore the scientific literature and dissemination sources to establish if such technologies have been introduced in this region. Likewise, this work highlights existing prototypes or systems that are to being used or that are still under development. A systematic search strategy was conducted by two different searches: the first one involves a rigorous literature search from the most relevant scientific digital repositories; the second one included telerehabilitation projects and programs retrieved by an advanced Google search. A total of 53 documents from six countries (Colombia, Brazil, Mexico, Ecuador, Chile and Argentina) were found. Most of them were focused on academic and research initiatives to develop in-home telerehabilitation technologies for pediatric and elderly populations affected by motor and functional impairment, cerebral palsy, neurocognitive disorders and stroke. The analysis of the findings revealed the need for a comprehensive approach that integrates health care and the social system to increase the current availability of telerehabilitation initiatives in Latin America

Recognition of elementary arm movements using orientation of a tri-axial accelerometer located near the wrist

In this paper we present a method for recognising three fundamental movements of the human arm (reach and retrieve, lift cup to mouth, rotation of the arm) by determining the orientation of a tri-axial accelerometer located near the wrist. Our objective is to detect the occurrence of such movements performed with the impaired arm of a stroke patient during normal daily activities as a means to assess their rehabilitation. The method relies on accurately mapping transitions of predefined, standard orientations of the accelerometer to corresponding elementary arm movements. To evaluate the technique, kinematic data was collected from four healthy subjects and four stroke patients as they performed a number of activities involved in a representative activity of daily living, 'making-a-cup-of-tea'. Our experimental results show that the proposed method can independently recognise all three of the elementary upper limb movements investigated with accuracies in the range 91–99% for healthy subjects and 70–85% for stroke patients

A wireless posture monitoring system for personalized home-based rehabilitation

We live in an aging society, an issue that will be exacerbated in the coming decades, due to low birth rates and increasing life expectancy. With the decline in physical and cognitive functions with age, it is of the utmost importance to maintain regular physical activity, in order to preserve an individual’s mobility, motor capabilities and coordination. Within this context, this paper describes the development of a wireless sensor network and its application in a human motion capture system based on wearable inertial and magnetic sensors. The goal is to enable, through continuous real-time monitoring, the creation of a personalized home-based rehabilitation system for the elderly population and/or injured people. Within this system, the user can benefit from an assisted mode, in which their movements can be compared to a reference motion model of the same movements, resulting in visual feedback alerts given by the application. This motion model can be created previously, in a ‘learning phase’, under supervision of a caregiver.Project “AAL4ALL”, co-financed by the European Community Fund FEDER through COMPETE – Programa Operacional Factores de Competitividade (POFC). This work is funded by FEDER funds through the COMPETE 2020 Programme and National Funds through FCT - Portuguese Foundation for Science and Technology under the projects UID/CTM/50025/2013 and UID/EEA/04436/2013.info:eu-repo/semantics/publishedVersio

Mobile Health Technologies

Mobile Health Technologies, also known as mHealth technologies, have emerged, amongst healthcare providers, as the ultimate Technologies-of-Choice for the 21st century in delivering not only transformative change in healthcare delivery, but also critical health information to different communities of practice in integrated healthcare information systems. mHealth technologies nurture seamless platforms and pragmatic tools for managing pertinent health information across the continuum of different healthcare providers. mHealth technologies commonly utilize mobile medical devices, monitoring and wireless devices, and/or telemedicine in healthcare delivery and health research. Today, mHealth technologies provide opportunities to record and monitor conditions of patients with chronic diseases such as asthma, Chronic Obstructive Pulmonary Diseases (COPD) and diabetes mellitus. The intent of this book is to enlighten readers about the theories and applications of mHealth technologies in the healthcare domain

Advancing biomedical engineering through a multi-modal sensor fusion system for enhanced physical training

In this paper, we introduce a multi-modal sensor fusion system designed for biomedical engineering, specifically geared toward optimizing physical training by collecting detailed body movement data. This system employs inertial measurement units, flex sensors, electromyography sensors, and Microsoft's Kinect V2 to generate an in-depth analysis of an individual's physical performance. We incorporate a gated recurrent unit- recurrent neural network algorithm to achieve highly accurate body and hand motion estimation, thus surpassing the performance of traditional machine learning algorithms in terms of accuracy, precision, recall, and F1 score. The system's integration with the PICO 4 VR environment creates a rich, interactive experience for physical training. Unlike conventional motion capture systems, our sensor fusion system is not limited to a fixed workspace, allowing users to engage in exercise within a flexible, free-form environment

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

International Conference on NeuroRehabilitation 2012

This volume 3, number 2 gathers a set of articles based on the most outstanding research on accessibility and disability issues that was presented in the International Conference on NeuroRehabilitation 2012 (ICNR).The articles’ research present in this number is centred on the analysis and/or rehabilitation of body impairment most due to brain injury and neurological disorders.JACCES thanks the collaboration of the ICNR members and the research authors and reviewers that have collaborated for making possible that issue

Rehabilitation Engineering

Population ageing has major consequences and implications in all areas of our daily life as well as other important aspects, such as economic growth, savings, investment and consumption, labour markets, pensions, property and care from one generation to another. Additionally, health and related care, family composition and life-style, housing and migration are also affected. Given the rapid increase in the aging of the population and the further increase that is expected in the coming years, an important problem that has to be faced is the corresponding increase in chronic illness, disabilities, and loss of functional independence endemic to the elderly (WHO 2008). For this reason, novel methods of rehabilitation and care management are urgently needed. This book covers many rehabilitation support systems and robots developed for upper limbs, lower limbs as well as visually impaired condition. Other than upper limbs, the lower limb research works are also discussed like motorized foot rest for electric powered wheelchair and standing assistance device