Dataset Information

Reaching and Grasping a Glass of Water by Locked-In ALS Patients through a BCI-Controlled Humanoid Robot.

ABSTRACT: Locked-in Amyotrophic Lateral Sclerosis (ALS) patients are fully dependent on caregivers for any daily need. At this stage, basic communication and environmental control may not be possible even with commonly used augmentative and alternative communication devices. Brain Computer Interface (BCI) technology allows users to modulate brain activity for communication and control of machines and devices, without requiring a motor control. In the last several years, numerous articles have described how persons with ALS could effectively use BCIs for different goals, usually spelling. In the present study, locked-in ALS patients used a BCI system to directly control the humanoid robot NAO (Aldebaran Robotics, France) with the aim of reaching and grasping a glass of water. Four ALS patients and four healthy controls were recruited and trained to operate this humanoid robot through a P300-based BCI. A few minutes training was sufficient to efficiently operate the system in different environments. Three out of the four ALS patients and all controls successfully performed the task with a high level of accuracy. These results suggest that BCI-operated robots can be used by locked-in ALS patients as an artificial alter-ego, the machine being able to move, speak and act in his/her place.

SUBMITTER: Spataro R

PROVIDER: S-EPMC5331030 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Reaching and Grasping a Glass of Water by Locked-In ALS Patients through a BCI-Controlled Humanoid Robot.

Spataro Rossella R Chella Antonio A Allison Brendan B Giardina Marcello M Sorbello Rosario R Tramonte Salvatore S Guger Christoph C La Bella Vincenzo V

Frontiers in human neuroscience 20170301

Locked-in Amyotrophic Lateral Sclerosis (ALS) patients are fully dependent on caregivers for any daily need. At this stage, basic communication and environmental control may not be possible even with commonly used augmentative and alternative communication devices. Brain Computer Interface (BCI) technology allows users to modulate brain activity for communication and control of machines and devices, without requiring a motor control. In the last several years, numerous articles have described ho ...[more]

PMID: 28298888

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Project description:BACKGROUND:Active upper-limb prostheses are used to restore important hand functionalities, such as grasping. In conventional approaches, a pattern recognition system is trained over a number of static grasping gestures. However, training a classifier in a static position results in lower classification accuracy when performing dynamic motions, such as reach-to-grasp. We propose an electromyography-based learning approach that decodes the grasping intention during the reaching motion, leading to a faster and more natural response of the prosthesis. METHODS AND RESULTS:Eight able-bodied subjects and four individuals with transradial amputation gave informed consent and participated in our study. All the subjects performed reach-to-grasp motions for five grasp types, while the elecromyographic (EMG) activity and the extension of the arm were recorded. We separated the reach-to-grasp motion into three phases, with respect to the extension of the arm. A multivariate analysis of variance (MANOVA) on the muscular activity revealed significant differences among the motion phases. Additionally, we examined the classification performance on these phases. We compared the performance of three different pattern recognition methods; Linear Discriminant Analysis (LDA), Support Vector Machines (SVM) with linear and non-linear kernels, and an Echo State Network (ESN) approach. Our off-line analysis shows that it is possible to have high classification performance above 80% before the end of the motion when with three-grasp types. An on-line evaluation with an upper-limb prosthesis shows that the inclusion of the reaching motion in the training of the classifier importantly improves classification accuracy and enables the detection of grasp intention early in the reaching motion. CONCLUSIONS:This method offers a more natural and intuitive control of prosthetic devices, as it will enable controlling grasp closure in synergy with the reaching motion. This work contributes to the decrease of delays between the user's intention and the device response and improves the coordination of the device with the motion of the arm.

Project description:INTRODUCTION:Intravenous insertion (IVI) is a very common procedure in the emergency department (ED). IVI is often painful and stressful for both children and their families. Currently, distraction therapy is not used as a standard of care for IVI in North America. We propose that interaction with a humanoid robot may effectively distract children during IVI thereby reducing their pain and distress. METHODS AND ANALYSIS:This randomised controlled superiority trial will be conducted in a Canadian paediatric ED. We plan to recruit 80 patients. Children will be eligible if they (1) are 6 to 11 years of age, (2) need an IVI, (3) are fully conscious and alert, (4) have sufficient knowledge of the English language to understand and complete the study assessments and (5) are accompanied by a legal guardian. Our primary objective is to compare patient-reported pain and distress with the use of distraction (via a humanoid robot) versus standard care in children. The primary outcomes will be (1) self-reported pain, as measured by the Faces Pain Scale-Revised and (2) observed distress, as measured by the Observational Scale of Behavioural Distress-Revised. Secondary outcomes will include (1) measuring parental anxiety, (2) examining the association between parental anxiety and child outcomes and (3) children's degree of engagement with the humanoid robot via the Intrinsic Motivation Inventory tool. First enrolment occurred in April 2017 and is ongoing. ETHICS AND DISSEMINATION:This study has been approved by the Health Research Ethics Board (University of Alberta). Informed consent to participate will be obtained from all participants' parents/guardian, in conjunction with assent from the participant themselves. This study data will be submitted for publication regardless of results. Purchase of the robot was facilitated through a Stollery Children's Hospital Foundation donation. Recruitment costs are supported by the Women and Children's Health Research Institute. TRIAL REGISTRATION NUMBER:NCT02997631; Pre-results.

Dataset Information

Reaching and Grasping a Glass of Water by Locked-In ALS Patients through a BCI-Controlled Humanoid Robot.

Publications

Reaching and Grasping a Glass of Water by Locked-In ALS Patients through a BCI-Controlled Humanoid Robot.

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