Factors influencing perceived function in the upper limb prosthesis user population

Abstract

Background: Patient-reported outcomes (PROs) can be used to evaluate perceived capacity of an individual in executing tasks in a natural environment with their prosthetic device. According to the World Health Organization International Classification of Health, Functioning, and Disability (ICF) models, there may be specific factors of a person, factors of assistive prosthetic technology, or factors related to the health condition or body function that affect their functioning and disability. However, an understanding of factors affecting an upper limb prosthesis user's perception of their ability to execute tasks in a natural environment is not well established. Objective: To use the ICF model to identify which health condition-related, body function, environmental, and personal factors influence activity as measured by perceived function in the upper limb prosthesis user population. Design: Quantitative clinical descriptive study. Setting: Clinical offices within outpatient private practice (removed for blinding). Participants: A sample of 101 participants with upper limb amputation who use a prosthetic device and were undergoing a prosthesis fitting process. Interventions: Not applicable. Main Outcome Measures: PROs on pain with/without a prosthesis, satisfaction, and perceived function derived from the Comprehensive Arm Prosthesis and Rehabilitation Outcomes Questionnaire. Results: Model coefficients indicate that with a unit increase in satisfaction (p < .001) and pain (p = .031) scores (with higher pain scores signifying less pain), the mean of perceived function increases by 0.66 and 0.47 units, respectively. Conversely, for individuals with elbow disarticulation, transhumeral, shoulder disarticulation, and interscapulothoracic amputations, the mean of perceived function decreases by 22.02 units (p = .006). Conclusions: Based on our sample, perceived function is significantly associated with satisfaction, pain, and amputation level. These findings could potentially help to inform initial clinical approach and targeted outcomes for patients based on these factors.

O Contributo Dos Fatores Humanos No Design De Produtos Para a Reabilitação De Amputados Produzidos Por Fabricação Aditiva

“…Considera-se assim, que o dispositivo não deve ser meramente visto como um produto de apoio, mas também como algo que potencializa boas emoções para o utilizador, originando um impacto positivo na interação entre ambos (Sansoni et al, 2016). Desta forma, o aumento da satisfação por parte do utilizador com o seu dispositivo leva a que exista também um aumento da perceção da sua função (Zhang et al, 2021). Assim, o amputado irá apresentar uma maior disposição para enfrentar os desafios que surgem durante o seu dia, como por exemplo desempenhar tarefas que poderia até achar impossível de serem realizadas após a amputação.…”

A Perspective on Prosthetic Hands Control: From the Brain to the Hand

“…[45,134]. Additionally, sEMG signals may also have a low spatial and temporal resolution, especially for fine and dexterous movements like grasping and manipulating objects [10,148]. These limitations may affect the functionality and performance of the control system and require feature extraction and enhancement techniques to improve them.…”

“…Standardization and validation of sEMG datasets and protocols are lacking, resulting in potential incomparability and irreproducibility between different studies and systems. Variations in data collection, preprocessing, segmentation, labelling, and evaluation, as well as user characteristics such as age, gender, health condition, and amputation level, can all impact the consistency and generalization of sEMG datasets and protocols [148].…”

“…Achieving good performance and accuracy with these algorithms may require high computational resources and training data [138]. The algorithms' complexity and power consumption can affect the control system's speed and efficiency, necessitating optimization and compression techniques to reduce them [148].…”

A scoping review of the application of motor learning principles to optimize myoelectric prosthetic hand control

“…Important to the design of any such guidelines is the realisation that the level of limb-loss and the type of device are important factors in need of consideration. For example, patients with more proximal levels of limb-loss have difficulties with bimanual tasks 100 , higher abandonment rates 101 , report less satisfaction 102 , and lower perceived functionality 103 compared to users of below elbow prostheses. There is also evidence that prosthetic devices with pattern-recognition technology can optimise intuitive control and alleviate cognitive demands compared to more traditional devices using direct control schemes 104,105 .…”