Affordable passive 3D-printed prosthesis for persons with partial hand amputation.

BACKGROUND AND AIM: Partial hand amputations are common in developing countries and have a negative impact on patients and their families' quality of life. The uniqueness of each partial hand amputation, coupled with the relatively high costs of prostheses, makes it challenging to provide suitable prosthetic solutions in developing countries. Current solutions often have long lead times and require a high level of expertise to produce. The aim of this study was to design and develop an affordable patient-specific partial hand prosthesis for developing countries. TECHNIQUE: The prosthesis was designed for a patient with transmetacarpal amputation (i.e. three amputated fingers and partial palm). The final design was passive, controlled by the contralateral hand, and utilized the advanced flexibility properties of thermoplastic polyurethane in a glove-like design that costs approximately 20 USD to fabricate. Quantitative and qualitative tests were conducted to assess performance of the device after the patient used the final design. A qualitative assessment was performed to gather the patient's feedback following a series of tests of grasp taxonomy. A quantitative assessment was performed through a grasp and lift test to measure the prosthesis' maximum load capacity. DISCUSSION: This study showed that the prosthesis enhanced the patient's manual handling capabilities, mainly in the form of grasp stability. The prosthesis was light weight and could be donned and doffed by the patient independently. Limitations include the need to use the contralateral hand to achieve grasping and low grasp strength. CLINICAL RELEVANCE: Persons with partial hand amputation in developing countries lack access to affordable functional prostheses, hindering their ability to participate in the community. 3D-printed prostheses can provide a low-cost solution that is adaptable to different amputation configurations.

sEMG feature evaluation for identification of elbow angle resolution in graded arm movement.

Automatic and accurate identification of elbow angle from surface electromyogram (sEMG) is essential for myoelectric controlled upper limb exoskeleton systems. This requires appropriate selection of sEMG features, and identifying the limitations of such a system.This study has demonstrated that it is possible to identify three discrete positions of the elbow; full extension, right angle, and mid-way point, with window size of only 200 milliseconds. It was seen that while most features were suitable for this purpose, Power Spectral Density Averages (PSD-Av) performed best. The system correctly classified the sEMG against the elbow angle for 100% cases when only two discrete positions (full extension and elbow at right angle) were considered, while correct classification was 89% when there were three discrete positions. However, sEMG was unable to accurately determine the elbow position when five discrete angles were considered. It was also observed that there was no difference for extension or flexion phases.