This Frontiers Research Topic covers both theoretical and experimental challenges in the application of robotics for the recovery of motor control and motor capabilities in individuals with impaired motor capabilities, as well as in the development of robotic systems and devices for independent living for disabled and elderly people. The main focus of the Research Topic is on novel research and applications motivated by human-centered design methodologies allowing: i) the adaptation of robot behavior to the patient's performance and particular bio-mechanical features, ii) the improvement of the safety of the interaction between robot and user, iii) the implementation of control strategies and variable impedance joints producing beneficial synergies between the rehabilitation robot and the human musculoskeletal system.

Magna Græcia University

Queen Mary University of London

Views

Article Views

Article Downloads

Frontiers in Robotics and AI

Biomedical Robotics

Frontiers in Neurorobotics

Human-Centered Rehabilitation and Assistive Robotics

Affecting 1 in 68, autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by social skill impairments. While prognosis can be significantly improved with intervention, few evidence-based interventions exist for social skill deficits in ASD. Existing interventions are resource-intensive, their outcomes vary widely for different individuals, and they often do not generalize to new contexts. Technology-aided intervention is a motivating, low-cost, and versatile approach for social skills training in ASD. Although early studies support the feasibility of technology-aided intervention, existing approaches have been criticized for teaching social skills through human-to-computer interaction, paradoxically leading to increased social isolation. To address this gap, we propose a system to help guide human-to-human interaction called Holli, a wearable technology to serve as a social skills coach for children with ASD. The Google Glass-based application listens to conversations and prompts the user with appropriate social responses. In this paper, we describe a usability study we conducted to determine the feasibility of using wearable technology to prompt children with ASD throughout social conversations. Fifteen children with ASD (mean age = 12.92 ± 2.33, verbal intelligent quotient = 103.3 ± 18.73) used the application while engaging in a restaurant-themed interaction with a research assistant. The application was evaluated on its effectiveness (i.e., how accurately the application responds), efficiency (i.e., how quickly the user and the application respond), and user satisfaction (based on a post-session questionnaire). All users were able to successfully complete the 10-turn exchange while using Holli. The results indicated the Holli accurately detected and recognized user utterance in real time. Participants reported positive experiences of using the application. To the best of our knowledge, this system is the first technology-aided intervention for ASD that employs human-to-human social coaching, and our results demonstrate the device is a viable medium for treatment delivery.

Affecting 1 in 68, autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by social skill impairments. While prognosis can be significantly improved with intervention, few evidence-based interventions exist for social skill deficits in ASD. Existing interventions are resource-intensive, their outcomes vary widely for different individuals, and they often do not generalize to new contexts. Technology-aided intervention is a motivating, low-cost, and versatile approach for social skills training in ASD. Although early studies support the feasibility of technology-aided intervention, existing approaches have been criticized for teaching social skills through human-to-computer interaction, paradoxically leading to increased social isolation. To address this gap, we propose a system to help guide human-to-human interaction called Holli, a wearable technology to serve as a social skills coach for children with ASD. The Google Glass-based application listens to conversations and prompts the user with appropriate social responses. In this paper, we describe a usability study we conducted to determine the feasibility of using wearable technology to prompt children with ASD throughout social conversations. Fifteen children with ASD (mean age = 12.92 &#xb1; 2.33, verbal intelligent quotient = 103.3 &#xb1; 18.73) used the application while engaging in a restaurant-themed interaction with a research assistant. The application was evaluated on its effectiveness (i.e., how accurately the application responds), efficiency (i.e., how quickly the user and the application respond), and user satisfaction (based on a post-session questionnaire). All users were able to successfully complete the 10-turn exchange while using Holli. The results indicated the Holli accurately detected and recognized user utterance in real time. Participants reported positive experiences of using the application. To the best of our knowledge, this system is the first technology-aided intervention for ASD that employs human-to-human social coaching, and our results demonstrate the device is a viable medium for treatment delivery.

Evaluating the Usability of a Wearable Social Skills Training Technology for Children with Autism Spectrum Disorder

Assistive robots have a great potential to address issues related to an aging population and an increased demand for caregiving. Successful deployment of robots working in close proximity with people requires consideration of both safety and human–robot interaction (HRI). One of the established activities of daily living where robots could play an assistive role is dressing. Using the correct force profile for robot control will be essential in this application of HRI requiring careful exploration of factors related to the user’s pose and the type of garments involved. In this paper, a Baxter robot was used to dress a jacket onto a mannequin and human participants considering several combinations of user pose and clothing type (base layers), while recording dynamic data from the robot, a load cell, and an IMU. We also report on suitability of these sensors for identifying dressing errors, e.g., fabric snagging. Data were analyzed by comparing the overlap of confidence intervals to determine sensitivity to dressing. We expand the analysis to include classification techniques such as decision tree and support vector machines using k-fold cross-validation. The 6-axis load cell successfully discriminated between clothing types with predictive model accuracies between 72 and 97%. Used independently, the IMU and Baxter sensors were insufficient to discriminate garment types with the IMU showing 40–72% accuracy, but when used in combination this pair of sensors achieved an accuracy similar to the more expensive load cell (98%). When observing dressing errors (snagging), Baxter’s sensors and the IMU data demonstrated poor sensitivity but applying machine learning methods resulted in model with high predicative accuracy and low false negative rates (≤5%). The results show that the load cell could be used independently for this application with good accuracy but a combination of the lower cost sensors could also be used without a significant loss in precision, which will be a key element in the robot control architecture for safe HRI.

Assistive robots have a great potential to address issues related to an aging population and an increased demand for caregiving. Successful deployment of robots working in close proximity with people requires consideration of both safety and human&#x2013;robot interaction (HRI). One of the established activities of daily living where robots could play an assistive role is dressing. Using the correct force profile for robot control will be essential in this application of HRI requiring careful exploration of factors related to the user&#x2019;s pose and the type of garments involved. In this paper, a Baxter robot was used to dress a jacket onto a mannequin and human participants considering several combinations of user pose and clothing type (base layers), while recording dynamic data from the robot, a load cell, and an IMU. We also report on suitability of these sensors for identifying dressing errors, e.g., fabric snagging. Data were analyzed by comparing the overlap of confidence intervals to determine sensitivity to dressing. We expand the analysis to include classification techniques such as decision tree and support vector machines using k-fold cross-validation. The 6-axis load cell successfully discriminated between clothing types with predictive model accuracies between 72 and 97%. Used independently, the IMU and Baxter sensors were insufficient to discriminate garment types with the IMU showing 40&#x2013;72% accuracy, but when used in combination this pair of sensors achieved an accuracy similar to the more expensive load cell (98%). When observing dressing errors (snagging), Baxter&#x2019;s sensors and the IMU data demonstrated poor sensitivity but applying machine learning methods resulted in model with high predicative accuracy and low false negative rates (&#x2264;5%). The results show that the load cell could be used independently for this application with good accuracy but a combination of the lower cost sensors could also be used without a significant loss in precision, which will be a key element in the robot control architecture for safe HRI.

A Quantitative Analysis of Dressing Dynamics for Robotic Dressing Assistance

Go Baby Go is a community-based outreach, research, and clinical treatment program that works with families, clinicians, service providers, and industry to provide pediatric equipment to children with disabilities for movement, mobility, and socialization. The purpose of the current technical report is to describe two innovative and novel extensions of the initial modified ride-on car technology that encourages self-directed mobility, participation, and function for young children with disabilities. The current report provides a description of the “sit-to-stand” and “throw-baby-throw” ride-on car technologies: (1) Sit-to-stand modified ride-on car technology: commercially available, battery-operated, ride-on cars are adapted by installing a large, easy-to-press activation switch that is placed on the steering wheel. The switch has a large surface area and turns on at the slightest touch allowing easier activation for children with disabilities. Common materials such as PVC pipe, swimming kickboards and fun noodles, and Velcro are used to build a custom seating system that provides optimum support for each child. There are no commercially available powered wheelchairs for children with disabilities from birth to 3 years old. An innovative sit-to-stand version of modified ride-on car will be presented and requires a child to stand up in order to activate the switch to encourage the physical skills of pulling from sit-to-stand, weight bearing, and balance; (2) Throw-baby-throw technology: children with disabilities that experience limited upper-extremity function are not able to throw an object. The throw-baby-throw technology includes modification of a commercially available, toy-based ball pitching machine that projects foam balls. We modified the toy so that it is switch activated and attached to a modified ride-on car. Our modified throwing device allows children with disabilities to engage in the fundamental motor skill of throwing. Both technologies presented in this technical report embrace the holistic view of the International Classification of Functioning, Disability, and Health framework by placing equal emphasis on the body structure and function, activity, and participation domains. Both technologies specifically target the advancement of physical skills while simultaneously providing opportunities to engage in experiences associated with activity and participation.

Go Baby Go is a community-based outreach, research, and clinical treatment program that works with families, clinicians, service providers, and industry to provide pediatric equipment to children with disabilities for movement, mobility, and socialization. The purpose of the current technical report is to describe two innovative and novel extensions of the initial modified ride-on car technology that encourages self-directed mobility, participation, and function for young children with disabilities. The current report provides a description of the “sit-to-stand” and “throw-baby-throw” ride-on car technologies: (1) Sit-to-stand modified ride-on car technology: commercially available, battery-operated, ride-on cars are adapted by installing a large, easy-to-press activation switch that is placed on the steering wheel. The switch has a large surface area and turns on at the slightest touch allowing easier activation for children with disabilities. Common materials such as PVC pipe, swimming kickboards and fun noodles, and Velcro are used to build a custom seating system that provides optimum support for each child. There are no commercially available powered wheelchairs for children with disabilities from birth to 3 years old. An innovative sit-to-stand version of modified ride-on car will be presented and requires a child to stand up in order to activate the switch to encourage the physical skills of pulling from sit-to-stand, weight bearing, and balance; (2) Throw-baby-throw technology: children with disabilities that experience limited upper-extremity function are not able to throw an object. The throw-baby-throw technology includes modification of a commercially available, toy-based ball pitching machine that projects foam balls. We modified the toy so that it is switch activated and attached to a modified ride-on car. Our modified throwing device allows children with disabilities to engage in the fundamental motor skill of throwing. Both technologies presented in this technical report embrace the holistic view of the International Classification of Functioning, Disability, and Health framework by placing equal emphasis on the body structure and function, activity, and participation domains. Both technologies specifically target the advancement of physical skills while simultaneously providing opportunities to engage in experiences associated with activity and participation.

Toy-Based Technologies for Children with Disabilities Simultaneously Supporting Self-Directed Mobility, Participation, and Function: A Tech Report

This paper investigates the effectiveness of three types of haptic feedback: normal stress, tangential force, and vibrotactile stimulation. Modern prosthetic limbs currently available on the market do not provide a wide range of sensory information to amputees, forcing amputees to mainly rely on visual attention when manipulating objects. We aim to develop a haptic system that can convey information to the central nervous system (CNS) through haptic feedback. To this end, we aim to find out which type of feedback performs best under static conditions, so that it can be used to restore a sense of grasping force to amputees. We tested the three main stimulation methods by inputting a series of five force magnitudes to each haptic device, so that the device applied the corresponding feedback to the participants’ finger pads. The participants then pressed on a force sensor, with the goal of applying the same level of force to a force sensor as they believed the haptic device had initially conveyed to them via their finger pads. While the subjects pressed on the force sensor, the haptic device applied a level of feedback to their forearms that corresponded to the pressure they were applying to the sensor. These tests provided fifteen numerical data per subject and a total of 180 trials for all twelve subjects. The end results indicate that even though all the stimulation methods provided a sufficient level of feedback, normal stress seems more effective than either tangential force or vibrotactile stimulation, at conveying the sense of pressure to the finger pad.

This paper investigates the effectiveness of three types of haptic feedback: normal stress, tangential force, and vibrotactile stimulation. Modern prosthetic limbs currently available on the market do not provide a wide range of sensory information to amputees, forcing amputees to mainly rely on visual attention when manipulating objects. We aim to develop a haptic system that can convey information to the central nervous system (CNS) through haptic feedback. To this end, we aim to find out which type of feedback performs best under static conditions, so that it can be used to restore a sense of grasping force to amputees. We tested the three main stimulation methods by inputting a series of five force magnitudes to each haptic device, so that the device applied the corresponding feedback to the participants&#x2019; finger pads. The participants then pressed on a force sensor, with the goal of applying the same level of force to a force sensor as they believed the haptic device had initially conveyed to them via their finger pads. While the subjects pressed on the force sensor, the haptic device applied a level of feedback to their forearms that corresponded to the pressure they were applying to the sensor. These tests provided fifteen numerical data per subject and a total of 180 trials for all twelve subjects. The end results indicate that even though all the stimulation methods provided a sufficient level of feedback, normal stress seems more effective than either tangential force or vibrotactile stimulation, at conveying the sense of pressure to the finger pad.

Comparing the Exteroceptive Feedback of Normal Stress, Skin Stretch, and Vibrotactile Stimulation for Restitution of Static Events

In this paper, we aim to investigate the effect of proprioceptive neuromuscular facilitation (PNF)-based rehabilitation for ankle plantar flexors spasticity by using a Robotic Ankle–foot Rehabilitation System (RARS). A modified robot-assisted system was proposed, and seven poststroke patients with hemiplegic spastic ankles participated in a 3-month robotic PNF training. Their impaired sides were used as the experimental group, while their unimpaired sides as the control group. A robotic intervention for the experimental group started from a 2-min passive stretching to warming-up or relaxing the soleus and gastrocnemius muscles and also ended with the same one. Then a PNF training session including 30 trials was activated between them. The rehabilitation trainings were carried out three times a week as an addition to their regular rehabilitation exercise. Passive range of motion, resistance torque, and stiffness were measured in both ankles before and after the interventions. The changes in Achilles tendon length, walking speed, and lower limb function were also evaluated by the same physician or physiotherapist for each participant. Biomechanical measurements before interventions showed significant difference between the experimental group and the control group due to ankle spasticity. For the control group, there was no significant difference in the 3 months with no robotic intervention. But for the experimental group, passive dorsiflexion range of motion increased (p < 0.01), resistance torque under different dorsiflexion angle levels (0°, 10°, and 20°) decreased (p < 0.05, p < 0.001, and p < 0.001, respectively), and quasi-static stiffness under different dorsiflexion angle levels (0°, 10°, and 20°) also decreased (p < 0.01, p < 0.001, and p < 0.001, respectively). Achilles’s tendon length shortened (p < 0.01), while its thickness showed no significant change (p > 0.05). The robotic rehabilitation also improved the muscle strength (p < 0.01) and muscle control performance (p < 0.001). In addition, improvements were observed in clinical and functional measurements, such as Timed Up-and-Go (p < 0.05), normal walking speed (p > 0.05), and fast walking speed (p < 0.05). These results indicated that the PNF-based robotic intervention could significantly alleviate lower limb spasticity and improve the motor function in chronic stroke participant. The robotic system could potentially be used as an effective tool in poststroke rehabilitation training.

In this paper, we aim to investigate the effect of proprioceptive neuromuscular facilitation (PNF)-based rehabilitation for ankle plantar flexors spasticity by using a Robotic Ankle–foot Rehabilitation System (RARS). A modified robot-assisted system was proposed, and seven poststroke patients with hemiplegic spastic ankles participated in a 3-month robotic PNF training. Their impaired sides were used as the experimental group, while their unimpaired sides as the control group. A robotic intervention for the experimental group started from a 2-min passive stretching to warming-up or relaxing the soleus and gastrocnemius muscles and also ended with the same one. Then a PNF training session including 30 trials was activated between them. The rehabilitation trainings were carried out three times a week as an addition to their regular rehabilitation exercise. Passive range of motion, resistance torque, and stiffness were measured in both ankles before and after the interventions. The changes in Achilles tendon length, walking speed, and lower limb function were also evaluated by the same physician or physiotherapist for each participant. Biomechanical measurements before interventions showed significant difference between the experimental group and the control group due to ankle spasticity. For the control group, there was no significant difference in the 3 months with no robotic intervention. But for the experimental group, passive dorsiflexion range of motion increased (p &lt; 0.01), resistance torque under different dorsiflexion angle levels (0°, 10°, and 20°) decreased (p &lt; 0.05, p &lt; 0.001, and p &lt; 0.001, respectively), and quasi-static stiffness under different dorsiflexion angle levels (0°, 10°, and 20°) also decreased (p &lt; 0.01, p &lt; 0.001, and p &lt; 0.001, respectively). Achilles’s tendon length shortened (p &lt; 0.01), while its thickness showed no significant change (p &gt; 0.05). The robotic rehabilitation also improved the muscle strength (p &lt; 0.01) and muscle control performance (p &lt; 0.001). In addition, improvements were observed in clinical and functional measurements, such as Timed Up-and-Go (p &lt; 0.05), normal walking speed (p &gt; 0.05), and fast walking speed (p &lt; 0.05). These results indicated that the PNF-based robotic intervention could significantly alleviate lower limb spasticity and improve the motor function in chronic stroke participant. The robotic system could potentially be used as an effective tool in poststroke rehabilitation training.