Assistive Devices and Clothing: Exploring Adaptive Clothing Needs for Women with Lower Limb Prostheses Using the FEA Model

This study aimed to comprehensively investigate the essential considerations in designing adaptive clothing for women with lower limb prostheses in Saudi Arabia. Employing a qualitative methodology, the research entailed semi-structured, in-depth interviews with women utilizing lower limb prostheses and prosthetic specialists. This approach was selected to unearth pivotal design prerequisites and comprehend the specific challenges these women encounter within the realm of clothing. The utilization of selective sampling facilitated the collection of intricate and valuable insights. A Functional, Expressive, and Aesthetic (FEA) User Needs model was utilized to scrutinize participant feedback. Functional requisites encompass ease of dressing and undressing, accessibility to the prosthetic limb, comfort, mobility with the prosthesis, and appropriate fit. Additionally, participants highlighted various expressive needs, including privacy preservation, modesty, camouflaging disability appearances, maintaining alignment with non-disabled women’s fashion, and considerations about the aesthetic aspects of garments.

Dynamic Lower-Limb Alignment Focusing on Gait Stability

Introduction: Prosthetic limbs must be developed with proper alignment to facilitate safe and efficient gait patterns. This study aimed to identify factors impacting clinically proper gait patterns by objectively evaluating them in persons with lower-limb amputations who use prosthetic limbs. Materials and Methods: This non-experimental descriptive study assessed 58 persons with amputation who used prosthetic limbs. The mechanical axis angle (MAA) of the lower limb during the heel contact, midstance, and toe-off phases and the angle between the tube and floor during the midstance phase were measured using coronal plane gait images. We also investigated whether the MAA and tube angle during the midstance phase have a multimodal distribution. In case of multimodal distributions, we tested for significant between-group differences in patient characteristics. Results: The MAA and tube angle in the coronal plane during the midstance phase had a bimodal distribution (mean 0°). There was a significant difference in the duration of prosthetic limb use between the MAA < 0° and ≥0° groups during the midstance phase. Deviations in the lower limb MAA between the heel contact and midstance phases were 3.3° ± 2.2° and 3.1° ± 2.3° for persons with lower limb amputations in the MAA Conclusions: In this study, prosthetic alignment during the midstance phase had a bimodal distribution. In both groups, deviations in the lower limb MAA were aligned to be approximately 3°.

A New EMG Decomposition Framework for Upper Limb Prosthetic Systems

Neural interfaces based on surface Electromyography(EMG)decomposition have been widely used in upper limb prosthetic systems.In the current EMG decomposition framework,most Blind Source Separation(BSS)algorithms require EMG with a large number of channels(generally larger than 64)as input,while users of prosthetic limbs can generally only provide less skin surface for electrode placement than healthy people.We performed decomposition tests to demonstrate the performance of the new framework with the simulated EMG signal.The results show that the new framework identified more Motor Units(MUs)compared to the control group and it is suitable for decomposing EMG signals with low channel numbers.In order to verify the application value of the new framework in the upper limb prosthesis system,we tested its performance in decomposing experimental EMG signals in force fitting experiments as well as pattern recognition experiments.The average Pearson coefficient between the fitted finger forces and the ground truth forces is 0.9079 and the average accuracy of gesture classification is 95.11%.The results show that the decomposition results obtained by the new framework can be used in the control of the upper limb prosthesis while only requiring EMG signals with fewer channels.