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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. 

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. 

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. 

This article provides a comprehensive narrative review of physical task-based assessments used to evaluate the multi-grasp dexterity and functional impact of varying control systems in pediatric and adult upper-limb prostheses. Our search returned 1,442 research articles from online databases, of which 25 tests—selected for their scientific rigor, evaluation metrics, and psychometric properties—met our review criteria. We observed that despite significant advancements in the mechatronics of upper-limb prostheses, these 25 assessments are the only validated evaluation methods that have emerged since the first measure in 1948. This not only underscores the lack of a consistently updated, standardized assessment protocol for new innovations, but also reveals an unsettling trend: as technology outpaces standardized evaluation measures, developers will often support their novel devices through custom, study-specific tests. These boutique assessments can potentially introduce bias and jeopardize validity. Furthermore, our analysis revealed that current validated evaluation methods often overlook the influence of competing interests on test success. Clinical settings and research laboratories differ in their time constraints, access to specialized equipment, and testing objectives, all of which significantly influence assessment selection and consistent use. Therefore, we propose a dual testing approach to address the varied demands of these distinct environments. Additionally, we found that almost all existing task-based assessments lack an integrated mechanism for collecting patient feedback, which we assert is essential for a holistic evaluation of upper-limb prostheses. Our review underscores the pressing need for a standardized evaluation protocol capable of objectively assessing the rapidly advancing prosthetic technologies across all testing domains.