A virtual hand assessment system for efficient outcome measures of hand rehabilitation

Previously held under moratorium from 1st December 2016 until 1st December 2021.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control

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

Construcción, pruebas técnicas y evaluación de un prototipo para el análisis de cargas posturales en la mano de trabajadores de oficina.

La construcción, pruebas técnicas y evaluación de un Prototipo para el análisis de cargas posturales en la mano de trabajadores de oficina, mediante el uso de MATLAB, con el fin de prevenir enfermedades profesionales. Utilizando la investigación bibliográfica identificaron los métodos validados actualmente para el análisis ergonómico como lo son: RULA, REBA y OWAS, además del método de interpolación de percentiles y la ley de Rohmert, con las cuales se profundizó y detalló de mejor manera el análisis. El diseño del Prototipo fue realizado considerando la comodidad y seguridad para el usuario, los sensores de flexión que sujeta y el peso del Prototipo. El Software desarrollado que maneja el Prototipo consta de una interfaz que grafica las cargas posturales de la mano en tiempo real, así mismo permite obtener el tiempo máximo de exposición, el percentil y determinar la existencia de ángulos riesgosos para la mano de la persona en estudio. El tamaño de muestra calculado resultó de 640 datos por sensor de flexión, a su vez esta fue tomada de trabajadores de oficina de Bienestar Politécnico de la Escuela Superior Politécnica de Chimborazo. Se obtuvo que los datos se comportan de manera cuadrática en todas las cargas posturales; el 84.33 % de los datos correspondientes a los ángulos en el movimiento de extensión en los trabajadores de oficina estudiados son de riesgo alto, así como el 78.70% correspondiente a los ángulos en el movimeinto de abducción. Además, se obtuvo que del 30% al 40% del tiempo total de trabajo se sostienen ángulos riesgosos. El Prototipo mide y procesa satisfactoriamente las cargas posturales de la mano de trabajadores de oficina , además es cómodo y no impide las laborales rutinarias del usuario, se recomienda profundizar la valoración de los resultados con médicos ocupacionales y con un software certificado.The construction, technical tests and evaluation of a Prototype for the analysis of the hand postural tremor in office workers through the use of MATLAB software in order to prevent occupational diseases. The current valid methods for ergonomic analysis such as: RULA (Rapid Upper Limb Assessment), REBA (Rapid Entire Body Assessment) and OWAS (Ovako Working Analysis System) were identified by using bibliographic research, in addition the percentile interpolation method and Rohmert's law were used to deepen and detail the analysis in a better way. The Prototype design was made taking into account the comfort and safety for the user, the bending sensors that holds it as well as the weight of the Prototype. The developed software which handles the prototype consists of an interface that plots the hand postural tremor in real time, also it allows to obtain the maximum exposure time and the percentile as well as determine the existence of risky angles for the hand of the person being tested. The calculated sample size was 640 data per bending sensor, this was taken from employees of the Polytechnic Welfare office at Escuela Superior Politécnica of Chimborazo. It was obtained that the data behave in a quadratic way in all postural tremors: 84.33% of the data corresponding to the angles in the extension movement, as well as the 78.70% of the data corresponding to the angles in the abduction movement in the office workers studied are high risk. In addition, it was obtained that from 30% to 40% of the total work time are risky angles. The prototype measures and processes the hand postural tremors of office workers in a satisfactory way, and also it is comfortable and does not impede the daily work of the user. It is recommended to deepen the results with occupational physicians as well as with a certified software

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

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

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 12th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2020, held in Leiden, The Netherlands, in September 2020. The 60 papers presented in this volume were carefully reviewed and selected from 111 submissions. The were organized in topical sections on haptic science, haptic technology, and haptic applications. This year's focus is on accessibility

Human Health Engineering Volume II

In this Special Issue on “Human Health Engineering Volume II”, we invited submissions exploring recent contributions to the field of human health engineering, i.e., technology for monitoring the physical or mental health status of individuals in a variety of applications. Contributions could focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing physiological variables, papers highlighting health-monitoring applications, and examples of control and process management applications for human health. In comparison to biomedical engineering, we envision that the field of human health engineering will also cover applications for healthy humans (e.g., sports, sleep, and stress), and thus not only contribute to the development of technology for curing patients or supporting chronically ill people, but also to more general disease prevention and optimization of human well-being