Principles of human movement augmentation and the challenges in making it a reality

Augmenting the body with artificial limbs controlled concurrently to one's natural limbs has long appeared in science fiction, but recent technological and neuroscientific advances have begun to make this possible. By allowing individuals to achieve otherwise impossible actions, movement augmentation could revolutionize medical and industrial applications and profoundly change the way humans interact with the environment. Here, we construct a movement augmentation taxonomy through what is augmented and how it is achieved. With this framework, we analyze augmentation that extends the number of degrees-of-freedom, discuss critical features of effective augmentation such as physiological control signals, sensory feedback and learning as well as application scenarios, and propose a vision for the field

Biosignal‐based human–machine interfaces for assistance and rehabilitation : a survey

As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignal‐based HMIs for assistance and rehabilitation to outline state‐of‐the‐art and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, full‐text), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An ever‐growing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIs’ complex-ity, so their usefulness should be carefully evaluated for the specific application

Recent developments in biofeedback for neuromotor rehabilitation

The original use of biofeedback to train single muscle activity in static positions or movement unrelated to function did not correlate well to motor function improvements in patients with central nervous system injuries. The concept of task-oriented repetitive training suggests that biofeedback therapy should be delivered during functionally related dynamic movement to optimize motor function improvement. Current, advanced technologies facilitate the design of novel biofeedback systems that possess diverse parameters, advanced cue display, and sophisticated control systems for use in task-oriented biofeedback. In light of these advancements, this article: (1) reviews early biofeedback studies and their conclusions; (2) presents recent developments in biofeedback technologies and their applications to task-oriented biofeedback interventions; and (3) discusses considerations regarding the therapeutic system design and the clinical application of task-oriented biofeedback therapy. This review should provide a framework to further broaden the application of task-oriented biofeedback therapy in neuromotor rehabilitation

Bioinspired robotic rehabilitation tool for lower limb motor learning after stroke

Mención Internacional en el título de doctorEsta tesis doctoral presenta, tras repasar la marcha humana, las principales patologíıas y condiciones que la afectan, y los distintos enfoques de rehabilitación con la correspondiente implicación neurofisiológica, el camino de investigación que desemboca en la herramienta robótica de rehabilitación y las terapias que se han desarrollado en el marco de los proyectos europeos BioMot: Smart Wearable Robots with Bioinspired Sensory-Motor Skills y HANK: European advanced exoskeleton for rehabilitation of Acquired Brain Damage (ABD) and/or spinal cord injury’s patients, y probado bajo el paraguas del proyecto europeo ASTONISH: Advancing Smart Optical Imaging and Sensing for Health y el proyecto nacional ASSOCIATE: A comprehensive and wearable robotics based approach to the rehabilitation and assistance to people with stroke and spinal cord injury.This doctoral thesis presents, after reviewing human gait, the main pathologies and conditions that affect it, and the different rehabilitation approaches with the corresponding neurophysiological implications, the research journey that leads to the development of the rehabilitation robotic tool, and the therapies that have been designed, within the framework of the European projects BioMot: Smart Wearable Robots with Bioinspired Sensory-Motor Skills and HANK: European advanced exoskeleton for rehabilitation of Acquired Brain Damage (ABD) and/or spinal cord injury’s patients and tested under the umbrella of the European project ASTONISH: Advancing Smart Optical Imaging and Sensing for Health and the national project ASSOCIATE: A comprehensive and wearable robotics based approach to the rehabilitation and assistance to people with stroke and spinal cord injury.This work has been carried out at the Neural Rehabilitation Group (NRG), Cajal Institute, Spanish National Research Council (CSIC). The research presented in this thesis has been funded by the Commission of the European Union under the BioMot project - Smart Wearable Robots with Bioinspired Sensory-Motor Skills (Grant Agreement number IFP7-ICT - 611695); under HANK Project - European advanced exoskeleton for rehabilitation of Acquired Brain Damage (ABD) and/or spinal cord injury’s patients (Grant Agreements number H2020-EU.2. - PRIORITY ’Industrial leadership’ and H2020-EU.3. - PRIORITY ’Societal challenges’ - 699796); also under the ASTONISH Project - Advancing Smart Optical Imaging and Sensing for Health (Grant Agreement number H2020-EU.2.1.1.7. - ECSEL - 692470); with financial support of Spanish Ministry of Economy and Competitiveness (MINECO) under the ASSOCIATE project - A comprehensive and wearable robotics based approach to the rehabilitation and assistance to people with stroke and spinal cord injury (Grant Agreement number 799158449-58449-45-514); and with grant RYC-2014-16613, also by Spanish Ministry of Economy and Competitiveness.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Fernando Javier Brunetti Fernández.- Secretario: Dorin Sabin Copaci.- Vocal: Antonio Olivier

Down-Conditioning of Soleus Reflex Activity using Mechanical Stimuli and EMG Biofeedback

Spasticity is a common syndrome caused by various brain and neural injuries, which can severely impair walking ability and functional independence. To improve functional independence, conditioning protocols are available aimed at reducing spasticity by facilitating spinal neuroplasticity. This down-conditioning can be performed using different types of stimuli, electrical or mechanical, and reflex activity measures, EMG or impedance, used as biofeedback variable. Still, current results on effectiveness of these conditioning protocols are incomplete, making comparisons difficult. We aimed to show the within-session task- dependent and across-session long-term adaptation of a conditioning protocol based on mechanical stimuli and EMG biofeedback. However, in contrast to literature, preliminary results show that subjects were unable to successfully obtain task-dependent modulation of their soleus short-latency stretch reflex magnitude

Proceedings XXIII Congresso SIAMOC 2023

Il congresso annuale della Società Italiana di Analisi del Movimento in Clinica (SIAMOC), giunto quest’anno alla sua ventitreesima edizione, approda nuovamente a Roma. Il congresso SIAMOC, come ogni anno, è l’occasione per tutti i professionisti che operano nell’ambito dell’analisi del movimento di incontrarsi, presentare i risultati delle proprie ricerche e rimanere aggiornati sulle più recenti innovazioni riguardanti le procedure e le tecnologie per l’analisi del movimento nella pratica clinica. Il congresso SIAMOC 2023 di Roma si propone l’obiettivo di fornire ulteriore impulso ad una già eccellente attività di ricerca italiana nel settore dell’analisi del movimento e di conferirle ulteriore respiro ed impatto internazionale. Oltre ai qualificanti temi tradizionali che riguardano la ricerca di base e applicata in ambito clinico e sportivo, il congresso SIAMOC 2023 intende approfondire ulteriori tematiche di particolare interesse scientifico e di impatto sulla società. Tra questi temi anche quello dell’inserimento lavorativo di persone affette da disabilità anche grazie alla diffusione esponenziale in ambito clinico-occupazionale delle tecnologie robotiche collaborative e quello della protesica innovativa a supporto delle persone con amputazione. Verrà infine affrontato il tema dei nuovi algoritmi di intelligenza artificiale per l’ottimizzazione della classificazione in tempo reale dei pattern motori nei vari campi di applicazione