Low cost exoskeleton manipulator using bidirectional triboelectric sensors enhanced multiple degree of freedom sensory system.

Rapid developments of robotics and virtual reality technology are raising the requirements of more advanced human-machine interfaces for achieving efficient parallel control. Exoskeleton as an assistive wearable device, usually requires a huge cost and complex data processing to track the multi-dimensional human motions. Alternatively, we propose a triboelectric bi-directional sensor as a universal and cost-effective solution to a customized exoskeleton for monitoring all of the movable joints of the human upper limbs with low power consumption. The corresponding movements, including two DOF rotations of the shoulder, twisting of the wrist, and the bending motions, are detected and utilized for controlling the virtual character and the robotic arm in real-time. Owing to the structural consistency between the exoskeleton and the human body, further kinetic analysis offers additional physical parameters without introducing other types of sensors. This exoskeleton sensory system shows a great potential of being an economic and advanced human-machine interface for supporting the manipulation in both real and virtual worlds, including robotic automation, healthcare, and training applications.

Moderate to Substantial Inter-Rater Reliability in the Assessment of Cranial Bone Mobility Restrictions.

Background: The World Health Organization benchmarks for osteopathic training consider cranial osteopathy as an important manual skill. Studies of cranial manual therapy have exhibited poor reliability. The aim of this study was to investigate the inter-rater reliability of the manual mobility tests of the spheno-occipital synchondrosis (SOS), and the temporal, parietal, and frontal bones, as assessed in osteopathic manual therapy. Methods: Twenty-one adults were assessed on a single day by three experienced osteopaths using a standard assessment protocol. Before data collection, the osteopaths participated in a consensus training, which included establishing the criteria for identifying a cranial bone mobility restriction; the application of the seven-step palpation method; a pretesting practice; a fine-tuning palpation training; and a calibration period before the assessment of the subjects. Three subjects were assessed simultaneously with the evaluators rotating to assess each subject. The evaluators were blinded to the subject by a curtain, and each other's assessments. Each bone was rated as restricted or not restricted. The authors applied the Landis and Koch classification to describe the magnitude of inter-rater reliability. Results: Moderate reliability was established for a lateral strain of the SOS (Fleiss' generalized kappa 0.48), substantial reliability was established for the other SOS strain patterns (Fleiss' generalized kappa 0.62-0.75), and almost perfect reliability for temporal, parietal, and frontal bone (Fleiss' generalized kappa 0.81-0.96). Conclusion: The results demonstrate consistency when three experienced osteopaths evaluate cranial bone mobility restrictions. The results highlight the importance of consensus training and rigorous methodology in manual therapy reliability studies.

Validation of Marker-Less System for the Assessment of Upper Joints Reaction Forces in Exoskeleton Users.

This paper presents the validation of a marker-less motion capture system used to evaluate the upper limb stress of subjects using exoskeletons for locomotion. The system fuses the human skeletonization provided by commercial 3D cameras with forces exchanged by the user to the ground through upper limbs utilizing instrumented crutches. The aim is to provide a low cost, accurate, and reliable technology useful to provide the trainer a quantitative evaluation of the impact of assisted gait on the subject without the need to use an instrumented gait lab. The reaction forces at the upper limbs' joints are measured to provide a validation focused on clinically relevant quantities for this application. The system was used simultaneously with a reference motion capture system inside a clinical gait analysis lab. An expert user performed 20 walking tests using instrumented crutches and force platforms inside the observed volume. The mechanical model was applied to data from the system and the reference motion capture, and numerical simulations were performed to assess the internal joint reaction of the subject's upper limbs. A comparison between the two results shows a root mean square error of less than 2% of the subject's body weight.

Real-Time Human Action Recognition with a Low-Cost RGB Camera and Mobile Robot Platform.

Human action recognition is an important research area in the field of computer vision that can be applied in surveillance, assisted living, and robotic systems interacting with people. Although various approaches have been widely used, recent studies have mainly focused on deep-learning networks using Kinect camera that can easily generate data on skeleton joints using depth data, and have achieved satisfactory performances. However, their models are deep and complex to achieve a higher recognition score; therefore, they cannot be applied to a mobile robot platform using a Kinect camera. To overcome these limitations, we suggest a method to classify human actions in real-time using a single RGB camera, which can be applied to the mobile robot platform as well. We integrated two open-source libraries, i.e., OpenPose and 3D-baseline, to extract skeleton joints on RGB images, and classified the actions using convolutional neural networks. Finally, we set up the mobile robot platform including an NVIDIA JETSON XAVIER embedded board and tracking algorithm to monitor a person continuously. We achieved an accuracy of 70% on the NTU-RGBD training dataset, and the whole process was performed on an average of 15 frames per second (FPS) on an embedded board system.

A Novel Method of Human Joint Prediction in an Occlusion Scene by Using Low-cost Motion Capture Technique.

Microsoft Kinect, a low-cost motion capture device, has huge potential in applications that require machine vision, such as human-robot interactions, home-based rehabilitation and clinical assessments. The Kinect sensor can track 25 key three-dimensional (3D) "skeleton" joints on the human body at 30 frames per second, and the skeleton data often have acceptable accuracy. However, the skeleton data obtained from the sensor sometimes exhibit a high level of jitter due to noise and estimation error. This jitter is worse when there is occlusion or a subject moves slightly out of the field of view of the sensor for a short period of time. Therefore, this paper proposed a novel approach to simultaneously handle the noise and error in the skeleton data derived from Kinect. Initially, we adopted classification processing to divide the skeleton data into noise data and erroneous data. Furthermore, we used a Kalman filter to smooth the noise data and correct erroneous data. We performed an occlusion experiment to prove the effectiveness of our algorithm. The proposed method outperforms existing techniques, such as the moving mean filter and traditional Kalman filter. The experimental results show an improvement of accuracy of at least 58.7%, 47.5% and 22.5% compared to the original Kinect data, moving mean filter and traditional Kalman filter, respectively. Our method provides a new perspective for Kinect data processing and a solid data foundation for subsequent research that utilizes Kinect.

May I Keep an Eye on Your Training? Gait Assessment Assisted by a Mobile Robot.

A successful rehabilitation after surgery in hip endoprosthetics comprises self-training of the lessons taught by physiotherapists. While doing this, immediate feedback to the patient about deviations from physiological gait patterns during training is important. Such immediate feedback also concerns the correct usage of forearm crutches in three-point gait. In the project ROGER, a mobile Socially Assistive Robot (SAR) to support patients after surgery in hip endoprosthetics is going to be developed. The current implementation status of the robotic application developed for the use in a real-world scenario is presented below.

Relationship Between Running Economy and Kinematic Parameters in Long-Distance Runners.

Pizzuto, F, Fonseca de Oliveira, C, Amorim Soares, TS, Rago, V, Silva, G, and Oliveira, J. Relationship between running economy and kinematic parameters in long-distance runners. J Strength Cond Res 33(7): 1921-1928, 2019-The purpose of this study was to explore the relationship between running economy (RE) and sagittal, frontal, and transverse plane kinematic parameters in long-distance runners. A secondary purpose was to identify the kinematic predictors of RE during running at the lowest RE value, representing an individual's most efficient running intensity. Twenty recreational long-distance runners ran 3 submaximal stages on a treadmill (65, 75, and 85% of velocity at maximum oxygen consumption). Respiratory data were collected using a portable gas analysis system. Kinematics were gathered using passive retroreflective markers and 8 high-resolution infrared cameras to collect the respective trajectories. Hip, knee, and ankle angles at foot strike and stance phase, as well as spatio-temporal parameters were calculated during each gait cycle. Knee flexion/extension range of motion (ROM), knee ab/adduction ROM, and hip ab/adduction ROM during the stance phase of the gait cycle showed positive moderate to large correlations with RE (r ± 90% confidence intervals = 0.51 ± 0.29; 0.49 ± 0.30; 0.53 ± 0.28, respectively). Knee and hip ab/adduction ROMs during the stance phase are predictors of RE, accounting for 44% of RE variance. Therefore, sagittal and frontal plane kinematics affect RE-inducing alterations in running performance. Coaches, athletic trainers, and anyone involved in running training prescription should consider a relationship between these parameters to ensure optimal technique and, consequently, to improve RE in recreational long-distance runners.

A biomechanical assessment of running with hallux unstable shoes of different material stiffness.

PURPOSE: Functional footwear with different unstable profiles has been widely used to mimic barefoot condition and offload plantar loading for pathological or injury prevention. However, little research investigates the effect of unstable structure on particular foot functions. In this study, a prototype of unstable shoe design with unstable element of different stiffness placed at the hallux (a regionalized rocker) was used. The primary objective was to analyse the biomechanical performance of running with hallux unstable shoes, aiming to potentially stimulate and increase the toe gripping function. METHODS: The lower limb kinematics and plantar pressure distribution were measured to comparatively analyse the soft (SS) and hard (SH) unstable shoes with flat control shoes (CS). RESULTS: The SS showed increased big toe and reduced forefoot plantar pressure. The SS led to similar lower limb kinematics to baseline CS except for reduced hip abduction, increased rotation range of motion (ROM), increased peak ankle plantar flexion and ROM. The SH presented significantly altered lower limb kinematics across hip, knee and ankle, and laterally distributed plantar pressure. CONCLUSIONS: Unstable shoes with soft material led to reduced medial metatarsal loading by increasing the support area and modified joint kinematics minimally. Unstable shoes with stiffer material presented compensatory kinematic movements across all joints and laterally shifted plantar loading distribution. These findings may provide implications on toe grip function training for foot pressure off-loading.

The LAMB gait analysis protocol: Definition and experimental assessment of operator-related variability.

Gait analysis has demonstrated to efficaciously support clinical investigations. The patterns of the outcome variables (joint angles, moments and powers) are characterized by an intrinsic and extrinsic variability. Particularly, extrinsic variability is induced by operator-dependent differences in markers' placement, with errors propagating non-linearly to alter outcome variable patterns. The aims of this study are (1) to consider a specific gait analysis protocol named LAMB and provide a description of its procedures, (2) to experimentally assess the between-operator and within-operator variability induced by operator-dependent marking of required anatomical landmarks and (3) to evidence how such inaccuracies propagates to the gait analysis kinematic and kinetic outcome variables. Six expert gait analysis operators performed LAMB anatomical landmarks marking on three healthy adult participants; moreover, one operator repeated three times the marking on one participant. The participants then performed a set of locomotor tasks including stair negotiation and heel- and toe-walking. An anatomical calibration approach let to register each marking and to compute, starting from one single raw data set, a set of outcome variables for each marking/operator. The between-operator variability of gait analysis outcome was assessed in terms of mean absolute variability to quantify offsets and minimal correlation coefficient to quantify patterns' similarity. The results evidence average minimal correlation coefficient ranging from 0.857 for moments to 0.907 for angles and average mean absolute variability accounted for few degrees in angular variables (worst between-operator mean absolute variability is 7.3°), while dynamic variables mean absolute variability, relative to the variable range, was below 5% for moment and below 10% for powers. The variability indexes are comparable to those related to previously published protocols and are independent from the considered task, thus suggesting that the LAMB is a reliable protocol suitable for the analysis of different locomotor tasks.

A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait.

Whether humans minimize metabolic energy in gait is unknown. Gradient-based optimization could be used to predict gait without using walking data but requires a twice differentiable metabolic energy model. Therefore, the metabolic energy model of Umberger et al. ( 2003 ) was adapted to be twice differentiable. Predictive simulations of a reaching task and gait were solved using this continuous model and by minimizing effort. The reaching task simulation showed that energy minimization predicts unrealistic movements when compared to effort minimization. The predictive gait simulations showed that objectives other than metabolic energy are also important in gait.

Assessment of pose repeatability and specimen repositioning of a robotic joint testing platform.

This paper describes the quantitative assessment of a robotic testing platform, consisting of an industrial robot and a universal force-moment sensor, via the design of fixtures used to hold the tibia and femur of cadaveric knees. This platform was used to study the contributions of different soft tissues and the ability of implants and reconstruction surgeries to restore normal joint functions, in previously published literature. To compare different conditions of human joints, it is essential to reposition specimens with high precision after they have been removed for a surgical procedure. Methods and experiments carried out to determine the pose repeatability and measure errors in repositioning specimens are presented. This was achieved using an optical tracking system (fusion Track 500, Atracsys Switzerland) to measure the position and orientation of bespoke rigid body markers attached to the tibial and femoral pots after removing and reinstalling them inside the rigs. The pose repeatability was then evaluated by controlling the robotic platform to move a knee joint repeatedly to/from a given pose while tracking the position and orientation of a rigid body marker attached to the tibial fixture. The results showed that the proposed design ensured a high repeatability in repositioning the pots with standard deviations for the computed distance and angle between the pots at both ends of the joint equal to 0.1mm, 0.01mm, 0.13° and 0.03° for the tibial and femoral fixtures respectively. Therefore, it is possible to remove and re-setup a joint with high precision. The results also showed that the errors in repositioning the robotic platform (that is: specimen path repeatability) were 0.11mm and 0.12°, respectively.

Inertial measurement systems for segments and joints kinematics assessment: towards an understanding of the variations in sensors accuracy.

BACKGROUND: Joints kinematics assessment based on inertial measurement systems, which include attitude and heading reference system (AHRS), are quickly gaining in popularity for research and clinical applications. The variety of the tasks and contexts they are used in require a deep understanding of the AHRS accuracy for optimal data interpretation. However, published accuracy studies on AHRS are mostly limited to a single task measured on a limited number of segments and participants. This study assessed AHRS sensors kinematics accuracy at multiple segments and joints through a variety of tasks not only to characterize the system's accuracy in these specific conditions, but also to extrapolate the accuracy results to a broader range of conditions using the characteristics of the movements (i.e. velocity and type of motion). Twenty asymptomatic adults ([Formula: see text] = 49.9) performed multiple 5 m timed up and go. Participants' head, upper trunk, pelvis, thigh, shank and foot were simultaneously tracked using AHRS and an optical motion capture system (gold standard). Each trial was segmented into basic tasks (sit-to-stand, walk, turn). RESULTS: At segment level, results revealed a mean root-mean-squared-difference [Formula: see text] varying between 1.1° and 5.5° according to the segment tracked and the task performed, with a good to excellent agreement between the systems. Relative sensor kinematics accuracy (i.e. joint) varied between 1.6° and 13.6° over the same tasks. On a global scheme, analysis of the effect of velocity on sensor kinematics accuracy showed that AHRS are better adapted to motions performed between 50°/s and 75°/s (roughly thigh and shank while walking). CONCLUSION: Results confirmed that pairing of modules to obtain joint kinematics affects the accuracy compared to segment kinematics. Overall, AHRS are a suitable solution for clinical evaluation of biomechanics under the multi-segment tasks performed although the variation in accuracy should be taken into consideration when judging the clinical meaningfulness of the observed changes.

The Influence of Pole Length on Performance, O2 Cost, and Kinematics in Double Poling.

PURPOSE: In the double-poling (DP) cross-country-skiing technique, propulsive forces are transferred solely through the poles. The aim of the current study was to investigate how pole length influences DP performance, O2 cost, and kinematics during treadmill roller skiing. METHODS: Nine male competitive cross-country skiers (24 ± 3 y, 180 ± 5 cm, 72 ± 5 kg, VO2max running 76 ± 6 mL · kg-1 · min-1) completed 2 identical test protocols using self-selected (84% ± 1% of body height) and long poles (self-selected + 7.5 cm; 88% ± 1% of body height) in a counterbalanced fashion. Each test protocol included a 5-min warm-up (2.5 m/s; 2.5°) and three 5-min submaximal sessions (3.0, 3.5, and 4.0 m/s; 2.5°) for assessment of O2 cost, followed by a selfpaced 1000-m time trial (~3 min, >5.0 m/s; 2.5°). Temporal patterns and kinematics were assessed using accelerometers and 2D video. RESULTS: Long poles reduced 1000-m time (mean ± 90% confidence interval; -1.0% ± 0.7%, P = .054) and submaximal O2 cost (-2.7% ± 1.0%, P = .002) compared with self-selected poles. The center-of-mass (CoM) vertical range of displacement tended to be smaller for long than for self-selected poles (23.3 ± 3.0 vs 24.3 ± 3.0 cm, P = .07). Cycle and reposition time did not differ between pole lengths at any speeds tested, whereas poling time tended to be shorter for self-selected than for long poles at the lower speeds (≤3.5 m/s, P ≤ .10) but not at the higher speeds (≥4.0 m/s, P ≥ .23). CONCLUSIONS: DP 1000-m time, submaximal O2 cost, and CoM vertical range of displacement were reduced in competitive cross-country skiers using poles 7.5 cm longer than self-selected ones.

To what extent is joint and muscle mechanics predicted by musculoskeletal models sensitive to soft tissue artefacts?

Musculoskeletal models are widely used to estimate joint kinematics, intersegmental loads, and muscle and joint contact forces during movement. These estimates can be heavily affected by the soft tissue artefact (STA) when input positional data are obtained using stereophotogrammetry, but this aspect has not yet been fully characterised for muscle and joint forces. This study aims to assess the sensitivity to the STA of three open-source musculoskeletal models, implemented in OpenSim. A baseline dataset of marker trajectories was created for each model from experimental data of one healthy volunteer. Five hundred STA realizations were then statistically generated using a marker-dependent model of the pelvis and lower limb artefact and added to the baseline data. The STA׳s impact on the musculoskeletal model estimates was finally quantified using a Monte Carlo analysis. The modelled STA distributions were in line with the literature. Observed output variations were comparable across the three models, and sensitivity to the STA was evident for most investigated quantities. Shape, magnitude and timing of the joint angle and moment time histories were not significantly affected throughout the entire gait cycle, whereas magnitude variations were observed for muscle and joint forces. Ranges of contact force variations differed between joints, with hip variations up to 1.8 times body weight observed. Variations of more than 30% were observed for some of the muscle forces. In conclusion, musculoskeletal simulations using stereophotogrammetry may be safely run when only interested in overall output patterns. Caution should be paid when more accurate estimated values are needed.

Instantaneous Metabolic Cost of Walking: Joint-Space Dynamic Model with Subject-Specific Heat Rate.

A subject-specific model of instantaneous cost of transport (ICOT) is introduced from the joint-space formulation of metabolic energy expenditure using the laws of thermodynamics and the principles of multibody system dynamics. Work and heat are formulated in generalized coordinates as functions of joint kinematic and dynamic variables. Generalized heat rates mapped from muscle energetics are estimated from experimental walking metabolic data for the whole body, including upper-body and bilateral data synchronization. Identified subject-specific energetic parameters-mass, height, (estimated) maximum oxygen uptake, and (estimated) maximum joint torques-are incorporated into the heat rate, as opposed to the traditional in vitro and subject-invariant muscle parameters. The total model metabolic energy expenditure values are within 5.7 ± 4.6% error of the measured values with strong (R2 > 0.90) inter- and intra-subject correlations. The model reliably predicts the characteristic convexity and magnitudes (0.326-0.348) of the experimental total COT (0.311-0.358) across different subjects and speeds. The ICOT as a function of time provides insights into gait energetic causes and effects (e.g., normalized comparison and sensitivity with respect to walking speed) and phase-specific COT, which are unavailable from conventional metabolic measurements or muscle models. Using the joint-space variables from commonly measured or simulated data, the models enable real-time and phase-specific evaluations of transient or non-periodic general tasks that use a range of (aerobic) energy pathway similar to that of steady-state walking.

Skeleton-Based Abnormal Gait Detection.

Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an approach for detecting abnormal human gait based on a normal gait model. Instead of employing the color image, silhouette, or spatio-temporal volume, our model is created based on human joint positions (skeleton) in time series. We decompose each sequence of normal gait images into gait cycles. Each human instant posture is represented by a feature vector which describes relationships between pairs of bone joints located in the lower body. Such vectors are then converted into codewords using a clustering technique. The normal human gait model is created based on multiple sequences of codewords corresponding to different gait cycles. In the detection stage, a gait cycle with normality likelihood below a threshold, which is determined automatically in the training step, is assumed as an anomaly. The experimental results on both marker-based mocap data and Kinect skeleton show that our method is very promising in distinguishing normal and abnormal gaits with an overall accuracy of 90.12%.

Haemarthrosis model in mice: BSS - Bleeding Severity Score assessment system.

INTRODUCTION: The prophylactic administration of clotting factor concentrate is currently the most effective strategy for the prevention of joint bleeding. As new agents with different mechanisms of action and administration schedules are developed, it will be important to study them in relevant preclinical models. AIM: The aim of this study was the standardization of a mouse haemarthrosis model in a haemophilia mouse and the development and validation of a comprehensive bleeding assessment system, the Bleeding Severity Score (BSS). METHODS AND RESULTS: Four outcome measurements were assessed, two of which, the extra-articular bleeding score and intra-articular bleeding score, were determined to be the most reliable and were summarized into a BSS which was validated using a mouse haemarthrosis variability model. CONCLUSION: Using this model, the haemostatic effect of prospective drugs can be assessed in a clinically relevant joint bleeding model and will significantly increase the value of preclinical studies.

Assessment of three-dimensional joint kinematics of the upper limb during simulated swimming using wearable inertial-magnetic measurement units.

The analysis of the joint kinematics during swimming plays a fundamental role both in sports conditioning and in clinical contexts. Contrary to the traditional video analysis, wearable inertial-magnetic measurements units (IMMUs) allow to analyse both the underwater and aerial phases of the swimming stroke over the whole length of the swimming pool. Furthermore, the rapid calibration and short data processing required by IMMUs provide coaches and athletes with an immediate feedback on swimming kinematics during training. This study aimed to develop a protocol to assess the three-dimensional kinematics of the upper limbs during swimming using IMMUs. Kinematics were evaluated during simulated dry-land swimming trials performed in the laboratory by eight swimmers. A stereo-photogrammetric system was used as the gold standard. The results showed high coefficient of multiple correlation (CMC) values, with median (first-third quartile) of 0.97 (0.93-0.95) and 0.99 (0.97-0.99) for simulated front-crawl and breaststroke, respectively. Furthermore, the joint angles were estimated with an accuracy increasing from distal to proximal joints, with wrist indices showing median CMC values always higher than 0.90. The present findings represent an important step towards the practical use of technology based on IMMUs for the kinematic analysis of swimming in applied contexts.

Gait assessment using the Microsoft Xbox One Kinect: Concurrent validity and inter-day reliability of spatiotemporal and kinematic variables.

The revised Xbox One Kinect, also known as the Microsoft Kinect V2 for Windows, includes enhanced hardware which may improve its utility as a gait assessment tool. This study examined the concurrent validity and inter-day reliability of spatiotemporal and kinematic gait parameters estimated using the Kinect V2 automated body tracking system and a criterion reference three-dimensional motion analysis (3DMA) marker-based camera system. Thirty healthy adults performed two testing sessions consisting of comfortable and fast paced walking trials. Spatiotemporal outcome measures related to gait speed, speed variability, step length, width and time, foot swing velocity and medial-lateral and vertical pelvis displacement were examined. Kinematic outcome measures including ankle flexion, knee flexion and adduction and hip flexion were examined. To assess the agreement between Kinect and 3DMA systems, Bland-Altman plots, relative agreement (Pearson's correlation) and overall agreement (concordance correlation coefficients) were determined. Reliability was assessed using intraclass correlation coefficients, Cronbach's alpha and standard error of measurement. The spatiotemporal measurements had consistently excellent (r≥0.75) concurrent validity, with the exception of modest validity for medial-lateral pelvis sway (r=0.45-0.46) and fast paced gait speed variability (r=0.73). In contrast kinematic validity was consistently poor to modest, with all associations between the systems weak (r<0.50). In those measures with acceptable validity, the inter-day reliability was similar between systems. In conclusion, while the Kinect V2 body tracking may not accurately obtain lower body kinematic data, it shows great potential as a tool for measuring spatiotemporal aspects of gait.

Design of a novel prosthetic socket: assessment of the thermal performance.

Prosthetic liners and sockets insulate the residual limb, causing excessive sweating and concomitant skin maceration. When coupled with atypical loading conditions, further dermatologic problems can arise. This can significantly reduce the quality of life of an amputee patient. Improving the design of the prosthetic socket has been proposed as a means of reestablishing a normal thermal environment around the residual limb. In this study, a prosthetic socket was modified by incorporating a helical cooling channel within the socket wall using additive manufacturing techniques. Two sockets were modeled: a control socket, and a modified socket containing a 0.48 cm diameter cooling channel. Computer simulations and bench-top testing were used to assess the design's ability to create a greater temperature differential across the socket wall. A greater temperature drop across the socket wall suggested that the socket could provide cooling benefits to the residual limb by allowing for heat to be drawn away from the limb. The temperature difference across the socket wall was calculated for both sockets in each aspect of the study. Both socket type (p=0.002) and location on the socket (p=0.014) were statistically significant factors affecting the temperature difference between inner and outer socket walls. Compared with the control socket, the modified socket containing a helical cooling channel exhibited greater temperature differences across its wall of 11.1 °C and 6.4 °C in the computer simulations and bench-top testing, respectively. This finding suggested that socket modifications, such as the cooling channel presented, could provide a beneficial cooling effect to an amputee patient's residual limb.