Search for: All records

Abstract In recent years, commercially available dexterous upper limb prostheses for children have begun to emerge. These devices derive control signals from surface electromyography (measure of affected muscle electrical activity, sEMG) to drive a variety of grasping motions. However, the ability for children with congenital upper limb deficiency to actuate their affected muscles to achieve naturalistic prosthetic control is not well understood, as compared to adults or children with acquired hand loss. To address this gap, we collected sEMG data from 9 congenital one-handed participants ages 8–20 years as they envisioned and attempted to perform 10 different movements with their missing hands. Seven sEMG electrodes were adhered circumferentially around the participant’s affected and unaffected limbs and participants mirrored the attempted missing hand motions with their intact side. To analyze the collected sEMG data, we used time and frequency domain analyses. We found that for the majority of participants, attempted hand movements produced detectable and consistent muscle activity, and the capacity to achieve this was not dissimilar across the affected and unaffected sides. These data suggest that children with congenital hand absence retain a degree of control over their affected muscles, which has important implications for translating and refining advanced prosthetic control technologies for children. 

Abstract Children with a unilateral congenital below elbow deficiency (UCBED) have one typical upper limb and one that lacks a hand, ending below the elbow at the proximal/mid forearm. UCBED is an isolated condition, and affected children otherwise develop normal sensorimotor control. Unlike adults with upper limb absence, the majority of whom have an acquired loss, children with UCBED never developed a hand, so their residual muscles have never actuated an intact limb. Their ability to purposefully modulate affected muscle activity is often assumed to be limited, and this assumption has influenced prosthetic design and prescription practices for this population as many modern devices derive control signals from affected muscle activity. To better understand the motor capabilities of the affected muscles, we used ultrasound imaging to study 6 children with UCBED. We examined the extent to which subjects activate their affected muscles when performing mirrored movements with their typical and missing hands. We demonstrate that all subjects could intentionally and consistently enact at least five distinct muscle patterns when attempting different missing hand movements (e.g., power grasp) and found similar performance across affected and typically developed limbs. These results suggest that although participants had never actuated the missing hand they could distinctively and consistently activate the residual muscle patterns associated with actions on the unaffected side. These findings indicate that motor control still develops in the absence of the normal effector, and can serve as a guide for developing prostheses that leverage the full extent of these children’s motor control capabilities. 

Children with Unilateral Congenital Below-Elbow Deficiencies (born without a hand, UCBED) have a high rate of prosthetic abandonment, pointing to unresolved challenges that may be distinct from those faced by adults with limb loss. There is limited knowledge of the motor control these children have over their affected muscles, a highly relevant question for effective dextrous prosthetic control. Our research aims to measure the extent of volitional muscle activation that exists in the residuum when children attempt moving their missing hand, with the goal of creating highly functional pediatric-specific prosthetic devices. In this work, we recruited 28 pediatric UCBED patients across four Shriners Hospital locations. We measured muscle activity using ultrasound imaging and surface electromyography while children attempted 10 missing-hand movements, then used machine learning to analyze the patterns of the affected and unaffected sides. Our algorithms predicted hand movements from residual muscle activity at over 80% accuracy in most cases, and well above chance in all participants. This indicates inherent muscular control which may be leveraged to develop more functional prosthetic devices tailored towards pediatric UCBED patients. 

Training for children who are prescribed myoelectric upper limb prostheses presents unique challenges in maintaining attention, motivation, and ultimately providing an enjoyable experience that is effective in developing the core motor skills required for device operation. From a clinical perspective, patient engagement is critical for maximizing functional outcomes, and from a research perspective, it can be vital to ensuring the quality of collected data. Therefore, our goal was to develop a training and research platform designed to both collect high-quality data from actively engaged participants and to provide them with a fun and engaging way to practice actuating the muscles relevant to myoelectric prosthetic control. “Ice is Nice” is a side scrolling video game that prompts children to perform a variety of movements with their missing hand, and the game is controlled using real-time measurement of their muscular activity. Our system is agnostic to muscle measurement systems, capable of using electromyography, force myography, and ultrasound-based control, among many others. As the game is played, data is logged to capture metrics relevant to game proficiency, human motor learning, and machine learning performance. Therefore, we suggest “Ice is Nice” provides a research and training platform with significant potential to support numerous follow-on studies conducted with children and adults. These studies aim to develop robust prosthetic control strategies, understand the effects of motor learning on prosthetic operation, and examine the functional capabilities of individuals operating upper limb prostheses. 

Although beginning to emerge, multiarticulate upper limb prostheses for children remain sparse despite the continued advancement of mechatronic technologies that have benefited adults with upper limb amputations. Upper limb prosthesis research is primarily focused on adults, even though rates of pediatric prosthetic abandonment far surpass those seen in adults. The implicit goal of a prosthesis is to provide effective functionality while promoting healthy social interaction. Yet most current pediatric devices offer a single degree of freedom open/close grasping function, a stark departure from the multiple grasp configurations provided in advanced adult devices. Although comparable child-sized devices are on the clinical horizon, understanding how to effectively translate these technologies to the pediatric population is vital. This includes exploring grasping movements that may provide the most functional benefits and techniques to control the newly available dexterity. Currently, no dexterous pediatric research platforms exist that offer open access to hardware and programming to facilitate the investigation and provision of multi-grasp function. Our objective was to deliver a child-sized multi-grasp prosthesis that may serve as a robust research platform. In anticipation of an open-source release, we performed a comprehensive set of benchtop and functional tests with common household objects to quantify the performance of our device. This work discusses and evaluates our pediatric-sized multiarticulate prosthetic hand that provides 6 degrees of actuation, weighs 177 g and was designed specifically for ease of implementation in a research or clinical-research setting. Through the benchtop and validated functional tests, the pediatric hand produced grasping forces ranging from 0.424–7.216 N and was found to be comparable to the functional capabilities of similar adult devices. As mechatronic technologies advance and multiarticulate prostheses continue to evolve, translating many of these emerging technologies may help provide children with more useful and functional prosthesis options. Effective translation will inevitably require a solid scientific foundation to inform how best to prescribe advanced prosthetic devices and control systems for children. This work begins addressing these current gaps by providing a much-needed research platform with supporting data to facilitate its use in laboratory and clinical research settings.