Background: Currently, there is no accurate method to objectively assess transtibial prosthetic socket fit. This study aims to evaluate the use of infrared thermography (IRT) to analyse temperature changes in response to pressure points, and their relation to pain and comfort assessments. This study also explores the reliability and agreement parameters of IRT.
Methods: A within-subject study was conducted on seven participants wearing a vacuum or pin suspension socket. Each participant was examined with two sockets: their prescribed socket (unmodified) and their prescribed socket modified with added pressure pads inside the prosthetic socket at the fibular head and distal tibia end. Thermal images were obtained after 10 minutes of walking with the unmodified socket (TW1), after a subsequent 15-minute resting period (TR1), after 10 minutes of walking with the modified socket (TW2), and after a second resting period (TR2). Difference maps showing temperature changes relative to the baseline (TR1) were created. Subjective assessments included localised pain and Socket Comfort Scores. Regions of interest (ROI) for temperature analysis were selected at the fibular head, distal tibia end, popliteal fossa, and gastrocnemius belly. Reliability and agreement were assessed using the Intraclass Correlation Coefficient (ICC), standard error of measurement (SEM), SEM%, smallest detectable change (SDC), SDC%, and Bland-Altman plots.
Results: Visual inspection and ROI temperature values revealed hotspots in 86% (6/7) of participants at the fibular head post-walking with the modified socket, contrasting with the unmodified socket in the majority of cases. Pain corresponded with the presence of hotspots at this location. Hotspots at the distal tibia end post-walking with the modified socket were observed in 43% (3/7) of participants, but without apparent difference from the unmodified socket. Only two-thirds of these coincided with reported pain. Reliability of IRT was very good to excellent across the residual limb and ROIs (ICC ≥ 0.85), except for fair reliability at the fibular head ROI (ICC 0.55). For TR1 and TR2 test-retest agreement, SEM ranged from 0.3 °C (1.0%) to 0.7 °C (2.1%), with SDC from 0.9 °C (2.8%) to 2.0 °C (5.9%). On the difference maps of unmodified and modified sockets, SEM ranged from 0.6 to 0.8 °C, and SDC from 1.7 to 2.1 °C.
Conclusion: Based on the observed thermal response to pressure in the majority of cases, IRT demonstrated potential in identifying peak pressure points and pain through increased temperature measurements at the fibular head, but had limited capability in detecting these at the distal tibia end. This limitation is likely due to differences in circulation, socket suspension effects, and uncertainty about the exerted pressure. Future research should simplify the protocol to enhance clinical applicability, enabling IRT to complement subjective socket fit assessments and improve prosthetic socket designs and patient outcomes.

Motor learning is a vital ability of the human brain in which multiple cortical areas like the primary motor cortex are involved. One way to investigate the fast motor learning brain dynamics is with use of electroencephalography (EEG). This non-invasive and mobile technique records continuous electrical activity on the brain cortex with a high temporal resolution. Although there has been considerable research into motor learning in humans, the mechanisms behind movement acquisition and execution are still largely unknown. A better understanding of motor learning is relevant to treatment and training in neurorehabilitation and sports medicine. The aim of this study was to provide insight into the neurophysiological mechanisms behind motor skill learning compared to motor execution. Motor skill learning is defined as the acquisition of a complex movement sequence by improving accuracy without comprising on speed. To investigate the neurophysiological mechanisms behind motor skill learning, 128-channel EEG was recorded in 20 young, right-handed, healthy participants while performing a motor skill learning task and a motor execution task. With use of adaptive mixture independent component analysis (AMICA), time-frequency analysis and equivalent dipole fitting source localisation, functional neurophysiological correlates of motor skill learning were investigated. Due to an excessive amount of electrical bridged electrodes, 12/20 participants were excluded from further analyses. In the 8 remaining participants, a cluster of independent components of electrical activity was located on the left primary motor cortex. In the motor learning task, lower β-frequency power was found in these components compared to the control task. This suggest that motor execution could be distinguished from motor learning on EEG by means of β activity in the left primary motor cortex. The results of this study can be used for future research on motor skill recovery in rehabilitation, motor learning in sports medicine and research on interventions to enhance motor learning, like non-invasive electrical brain stimulation.