A Deep Learning Model for Markerless Pose Estimation Based on Keypoint Augmentation: What Factors Influence Errors in Biomechanical Applications?

In biomechanics, movement is typically recorded by tracking the trajectories of anatomical landmarks previously marked using passive instrumentation, which entails several inconveniences. To overcome these disadvantages, researchers are exploring different markerless methods, such as pose estimation networks, to capture movement with equivalent accuracy to marker-based photogrammetry. However, pose estimation models usually only provide joint centers, which are incomplete data for calculating joint angles in all anatomical axes. Recently, marker augmentation models based on deep learning have emerged. These models transform pose estimation data into complete anatomical data. Building on this concept, this study presents three marker augmentation models of varying complexity that were compared to a photogrammetry system. The errors in anatomical landmark positions and the derived joint angles were calculated, and a statistical analysis of the errors was performed to identify the factors that most influence their magnitude. The proposed Transformer model improved upon the errors reported in the literature, yielding position errors of less than 1.5 cm for anatomical landmarks and 4.4 degrees for all seven movements evaluated. Anthropometric data did not influence the errors, while anatomical landmarks and movement influenced position errors, and model, rotation axis, and movement influenced joint angle errors.

Protocol for Forearm Pronosupination Strength Measuring in Different Postures: Reliability and Influence of Relevant Factors.

IMPORTANCE: Despite the importance of pronosupination strength, which is key in daily activities, current evaluation protocols are disparate, and results differ regarding the influence of factors such as gender, age, limb dominance, or posture. OBJECTIVE: To design a reliable device to measure pronation and supination torques in different forearm positions, considering the influence of gender, age, and limb dominance. DESIGN: Reliability study with analysis of intrarater and interrater repeatability and examination of the influence of different factors on the strength of pronation and supination. SETTING: Biomechanical analysis laboratory of the Instituto de Biomecánica de Valencia. PARTICIPANTS: Convenience sample of 39 healthy male and female participants, ages 18 to 65 yr. OUTCOMES AND MEASURES: Pronation strength and supination strength were studied in five forearm positions: 30° and 60° of supination, neutral rotation, and 30° and 60° of pronation. The influence of gender, age, and limb dominance was studied using repeated-measures analysis of variance. Intrarater and interrater reliabilities were studied in 17 participants, and the intraclass correlation coefficients (ICCs) were calculated from three measurement sessions. RESULTS: Except for 60° of pronation, all ICCs ranged from .72 to .97. Gender, limb dominance, and posture significantly affected pronosupination strength (p < .05), with the highest supination strength at 60° of pronation and the highest pronation strength at 60° of supination. CONCLUSIONS AND RELEVANCE: In using this reliable pronosupination torque assessment device and standardized protocol in the clinical setting, clinicians must consider the influence of gender, limb dominance, and forearm posture. What This Article Adds: The results of this study will allow occupational therapists to establish differences between patients' functionality in comparison with healthy individuals and to design recovery treatments and facilitate performance of manual tasks, considering which are the most advantageous positions to exert force. Furthermore, the developed device can be used to monitor the evolution of these torques in an objective and reliable manner.

A model to differentiate WAD patients and people with abnormal pain behaviour based on biomechanical and self-reported tests.

The prevalence of malingering among individuals presenting whiplash-related symptoms is significant and leads to a huge economic loss due to fraudulent injury claims. Various strategies have been proposed to detect malingering and symptoms exaggeration. However, most of them have been not consistently validated and tested to determine their accuracy in detecting feigned whiplash. This study merges two different approaches to detect whiplash malingering (the mechanical approach and the qualitative analysis of the symptomatology) to obtain a malingering detection model based on a wider range of indices, both biomechanical and self-reported. A sample of 46 malingerers and 59 genuine clinical patients was tested using a kinematic test and a self-report questionnaire asking about the presence of rare and impossible symptoms. The collected measures were used to train and validate a linear discriminant analysis (LDA) classification model. Results showed that malingerers were discriminated from genuine clinical patients based on a greater proportion of rare symptoms vs. possible self-reported symptoms and slower but more repeatable neck motions in the biomechanical test. The fivefold cross-validation of the LDA model yielded an area under the curve (AUC) of 0.84, with a sensitivity of 77.8% and a specificity of 84.7%.

Model of soft tissue artifact propagation to joint angles in human movement analysis.

This work describes the kinematic laws that govern the transmission of soft tissue artifact errors to kinematic variables in the analysis of human movements. Artifacts are described as relative translations and rotations of the marker cluster over the bone, and a set of explicit expressions is defined to account for the effect of that relative motion on different representations of rotations: the rotation around the screw axis, or rotation vector, and three Euler angle sequences (XY'Z, YX'Y″, ZX'Y″). Although the error transmission is nonlinear in all cases, the effect of artifacts is greater on Euler sequences than on the rotation vector. Specifically, there are crosstalk effects in Euler sequences that amplify the errors near singular configurations. This fact is an additional source of variability in studies that describe artifacts by comparing the Euler angles obtained from skin markers, with the angles of an artifact-free gold standard. The transmission of errors to rotation vector coordinates is less variable or dependent on the type of motion. This model has been tested in an experiment with a deformable mechanical model with a spherical joint.

Correction of joint angles from Kinect for balance exercising and assessment.

The new generation of videogame interfaces such as Microsoft's Kinect opens the possibility of implementing exercise programs for physical training, and of evaluating and reducing the risks of elderly people falling. However, applications such as these might require measurements of joint kinematics that are more robust and accurate than the standard output given by the available middleware. This article presents a method based on particle filters for calculating joint angles from the positions of the anatomical points detected by PrimeSense's NITE software. The application of this method to the measurement of lower limb kinematics reduced the error by one order of magnitude, to less than 10°, except for hip axial rotation, and it was advantageous over inverse kinematic analysis, in ensuring a robust and smooth solution without singularities, when the limbs are out-stretched and anatomical landmarks are aligned.

Positioning errors of anatomical landmarks identified by fixed vertices in homologous meshes.

BACKGROUND: Human movement analysis is usually achieved by tracking markers attached to anatomical landmarks with photogrammetry. Such marker-based systems have disadvantages that have led to the development of markerless procedures, although their accuracy is not usually comparable to that of manual palpation procedures. New motion acquisition systems, such as 3D temporal scanners, provide homologous meshes that can be exploited for this purpose. RESEARCH QUESTION: Can fixed vertices of a homologous mesh be used to identify anatomical landmarks with an accuracy equivalent to that of manual palpation? METHODS: We used 3165 human shape scans from the CAESAR dataset, with labelled locations of anatomical landmarks. First, we fitted a template mesh to the scans, and assigned a vertex of that mesh to 53 anatomical landmarks in all subjects. Then we defined a nominal vertex for each landmark, as the more centred vertex out of the set assigned for that landmark. We calculated the errors of the template-fitting and the nominal vertex determination procedures, and analysed their relationship to subject's sex, height and body mass index, as well as their size compared to manual palpation errors. RESULTS: The template-fitting errors were below 5 mm, and the nominal vertex determination errors reached maximum values of 24 mm. Except for the trochanter, those errors were the same order of magnitude or smaller than inter-examiner errors of lower limb landmarks. Errors increased with height and body mass index, and were smaller for men than for women of the same height and body mass index. SIGNIFICANCE: We defined a set of vertices for 53 anatomical landmarks in a homologous mesh, which yields location errors comparable to those obtained by manual palpation for the majority of landmarks. We also quantified how the subject's sex and anthropometric features can affect the size of those errors.

Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review.

BACKGROUND: Recent advances in natural language processing (NLP) have heightened the interest of the medical community in its application to health care in general, in particular to stroke, a medical emergency of great impact. In this rapidly evolving context, it is necessary to learn and understand the experience already accumulated by the medical and scientific community. OBJECTIVE: The aim of this scoping review was to explore the studies conducted in the last 10 years using NLP to assist the management of stroke emergencies so as to gain insight on the state of the art, its main contexts of application, and the software tools that are used. METHODS: Data were extracted from Scopus and Medline through PubMed, using the keywords "natural language processing" and "stroke." Primary research questions were related to the phases, contexts, and types of textual data used in the studies. Secondary research questions were related to the numerical and statistical methods and the software used to process the data. The extracted data were structured in tables and their relative frequencies were calculated. The relationships between categories were analyzed through multiple correspondence analysis. RESULTS: Twenty-nine papers were included in the review, with the majority being cohort studies of ischemic stroke published in the last 2 years. The majority of papers focused on the use of NLP to assist in the diagnostic phase, followed by the outcome prognosis, using text data from diagnostic reports and in many cases annotations on medical images. The most frequent approach was based on general machine learning techniques applied to the results of relatively simple NLP methods with the support of ontologies and standard vocabularies. Although smaller in number, there has been an increasing body of studies using deep learning techniques on numerical and vectorized representations of the texts obtained with more sophisticated NLP tools. CONCLUSIONS: Studies focused on NLP applied to stroke show specific trends that can be compared to the more general application of artificial intelligence to stroke. The purpose of using NLP is often to improve processes in a clinical context rather than to assist in the rehabilitation process. The state of the art in NLP is represented by deep learning architectures, among which Bidirectional Encoder Representations from Transformers has been found to be especially widely used in the medical field in general, and for stroke in particular, with an increasing focus on the processing of annotations on medical images.

Accuracy of a 3D temporal scanning system for gait analysis: Comparative with a marker-based photogrammetry system.

BACKGROUND: Combining the accuracy of marker-based stereophotogrammetry and the usability and comfort of markerless human movement analysis is a difficult challenge. 3D temporal scanners are a promising solution, since they provide moving meshes with thousands of vertices that can be used to analyze human movements. RESEARCH QUESTION: Can a 3D temporal scanner be used as a markerless system for gait analysis with the same accuracy as traditional, marker-based stereophotogrammetry systems? METHODS: A comparative study was carried out using a 3D temporal scanner synchronized with a marker-based stereophotogrammetry system. Two gait cycles of twelve healthy adults were measured simultaneously, extracting the positions of key anatomical points from both systems, and using them to analyze the 3D kinematics of the pelvis, right hip and knee joints. Measurement differences of marker positions and joint angles were described by their root mean square. A t-test was performed to rule out instrumental errors, and an F-test to evaluate the amplifications of marker position errors in dynamic conditions. RESULTS: The differences in 3D landmark positions were between 1.9 and 2.4 mm in the reference pose. Marker position errors were significantly increased during motion in the medial-lateral and vertical directions. The angle relative errors were between 3% and 43% of the range of motion, with the greatest difference being observed in hip axial rotation. SIGNIFICANCE: The differences in the results obtained between the 3D temporal scanner and the marker-based system were smaller than the usual errors due to lack of accuracy in the manual positioning of markers on anatomical landmarks and to soft-tissue artefacts. That level of accuracy is greater than other markerless systems, and proves that such technology is a good alternative to traditional, marker-based motion capture.

Relationship between neck motion and self-reported pain in patients with whiplash associated disorders during the acute phase.

BACKGROUND: Biomechanical measures quantify motor control and functional deficits in Whiplash Associated Disorders (WAD), but few studies relate those measures to the clinical scales that are routinely used to assess patients. Most studies are limited to chronic neck pain, and report poor to moderate correlations. OBJECTIVE: To define a statistical model that relates measures of neck kinematics with clinical scales of neck pain, in WAD patients during the rehabilitation process in the acute phase (less than 3 months since the accident). METHODS: 96 WAD patients self-assessed their pain using VAS and NPQ, and passed neck motion tests as part of their rehabilitation program. Four regression models were fitted to analyze the effects of the measured kinematic parameters and subject-specific characteristics on VAS and NPQ. Model errors were compared to minimal clinically significant differences. RESULTS: Multiple correlation coefficients of the models were between 0.74 and 0.90. More than 66% of that correlation was accounted for by subject-specific factors, and most of the other half by the measured kinematic parameters. Range of motion of flexion-extension and axial rotation, and harmonicity of flexion-extension, where the variables most consistently related to the decrease of pain. The error of the models was within the MCSD in more than 50% of the observations. CONCLUSIONS: Part of the individual progression of pain and pain-related disability in acute WAD patients, as rated by NPQ and VAS, can be mapped to objective kinematic parameters of neck mobility tests, like ranges of motion, velocities, repeatability and harmonicity of movements.

The My Active and Healthy Aging (My-AHA) ICT platform to detect and prevent frailty in older adults: Randomized control trial design and protocol.

INTRODUCTION: Frailty increases the risk of poor health outcomes, disability, hospitalization, and death in older adults and affects 7%-12% of the aging population. Secondary impacts of frailty on psychological health and socialization are significant negative contributors to poor outcomes for frail older adults. METHOD: The My Active and Healthy Aging (My-AHA) consortium has developed an information and communications technology-based platform to support active and healthy aging through early detection of prefrailty and provision of individually tailored interventions, targeting multidomain risks for frailty across physical activity, cognitive activity, diet and nutrition, sleep, and psychosocial activities. Six hundred adults aged 60 years and older will be recruited to participate in a multinational, multisite 18-month randomized controlled trial to test the efficacy of the My-AHA platform to detect prefrailty and the efficacy of individually tailored interventions to prevent development of clinical frailty in this cohort. A total of 10 centers from Italy, Germany, Austria, Spain, United Kingdom, Belgium, Sweden, Japan, South Korea, and Australia will participate in the randomized controlled trial. RESULTS: Pilot testing (Alpha Wave) of the My-AHA platform and all ancillary systems has been completed with a small group of older adults in Europe with the full randomized controlled trial scheduled to commence in 2018. DISCUSSION: The My-AHA study will expand the understanding of antecedent risk factors for clinical frailty so as to deliver targeted interventions to adults with prefrailty. Through the use of an information and communications technology platform that can connect with multiple devices within the older adult's own home, the My-AHA platform is designed to measure an individual's risk factors for frailty across multiple domains and then deliver personalized domain-specific interventions to the individual. The My-AHA platform is technology-agnostic, enabling the integration of new devices and sensor platforms as they emerge.

Analytical study of the effects of soft tissue artefacts on functional techniques to define axes of rotation.

The accurate location of the main axes of rotation (AoR) is a crucial step in many applications of human movement analysis. There are different formal methods to determine the direction and position of the AoR, whose performance varies across studies, depending on the pose and the source of errors. Most methods are based on minimizing squared differences between observed and modelled marker positions or rigid motion parameters, implicitly assuming independent and uncorrelated errors, but the largest error usually results from soft tissue artefacts (STA), which do not have such statistical properties and are not effectively cancelled out by such methods. However, with adequate methods it is possible to assume that STA only account for a small fraction of the observed motion and to obtain explicit formulas through differential analysis that relate STA components to the resulting errors in AoR parameters. In this paper such formulas are derived for three different functional calibration techniques (Geometric Fitting, mean Finite Helical Axis, and SARA), to explain why each technique behaves differently from the others, and to propose strategies to compensate for those errors. These techniques were tested with published data from a sit-to-stand activity, where the true axis was defined using bi-planar fluoroscopy. All the methods were able to estimate the direction of the AoR with an error of less than 5°, whereas there were errors in the location of the axis of 30-40mm. Such location errors could be reduced to less than 17mm by the methods based on equations that use rigid motion parameters (mean Finite Helical Axis, SARA) when the translation component was calculated using the three markers nearest to the axis.

The reliability of humerothoracic angles during arm elevation depends on the representation of rotations.

The reliability of joint rotation measurements is an issue of major interest, especially in clinical applications. The effect of instrumental errors and soft tissue artifacts on the variability of human motion measures is well known, but the influence of the representation of joint motion has not yet been studied. The aim of the study was to compare the within-subject reliability of three rotation formalisms for the calculation of the shoulder elevation joint angles. Five repetitions of humeral elevation in the scapular plane of 27 healthy subjects were recorded using a stereophotogrammetry system. The humerothoracic joint angles were calculated using the YX'Y" and XZ'Y" Euler angle sequences and the attitude vector. A within-subject repeatability study was performed for the three representations. ICC, SEM and CV were the indices used to estimate the error in the calculation of the angle amplitudes and the angular waveforms with each method. Excellent results were obtained in all representations for the main angle (elevation), but there were remarkable differences for axial rotation and plane of elevation. The YX'Y" sequence generally had the poorest reliability in the secondary angles. The XZ'Y' sequence proved to be the most reliable representation of axial rotation, whereas the attitude vector had the highest reliability in the plane of elevation. These results highlight the importance of selecting the method used to describe the joint motion when within-subjects reliability is an important issue of the experiment. This may be of particular importance when the secondary angles of motions are being studied.

ICT-based system to predict and prevent falls (iStoppFalls): results from an international multicenter randomized controlled trial.

BACKGROUND: Falls and fall-related injuries are a serious public health issue. Exercise programs can effectively reduce fall risk in older people. The iStoppFalls project developed an Information and Communication Technology-based system to deliver an unsupervised exercise program in older people's homes. The primary aims of the iStoppFalls randomized controlled trial were to assess the feasibility (exercise adherence, acceptability and safety) of the intervention program and its effectiveness on common fall risk factors. METHODS: A total of 153 community-dwelling people aged 65+ years took part in this international, multicentre, randomized controlled trial. Intervention group participants conducted the exercise program for 16 weeks, with a recommended duration of 120 min/week for balance exergames and 60 min/week for strength exercises. All intervention and control participants received educational material including advice on a healthy lifestyle and fall prevention. Assessments included physical and cognitive tests, and questionnaires for health, fear of falling, number of falls, quality of life and psychosocial outcomes. RESULTS: The median total exercise duration was 11.7 h (IQR = 22.0) over the 16-week intervention period. There were no adverse events. Physiological fall risk (Physiological Profile Assessment, PPA) reduced significantly more in the intervention group compared to the control group (F1,127 = 4.54, p = 0.035). There was a significant three-way interaction for fall risk assessed by the PPA between the high-adherence (>90 min/week; n = 18, 25.4 %), low-adherence (<90 min/week; n = 53, 74.6 %) and control group (F2,125 = 3.12, n = 75, p = 0.044). Post hoc analysis revealed a significantly larger effect in favour of the high-adherence group compared to the control group for fall risk (p = 0.031), postural sway (p = 0.046), stepping reaction time (p = 0.041), executive functioning (p = 0.044), and quality of life (p for trend = 0.052). CONCLUSIONS: The iStoppFalls exercise program reduced physiological fall risk in the study sample. Additional subgroup analyses revealed that intervention participants with better adherence also improved in postural sway, stepping reaction, and executive function. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry Trial ID: ACTRN12614000096651 International Standard Randomised Controlled Trial Number: ISRCTN15932647.

The design of a purpose-built exergame for fall prediction and prevention for older people.

BACKGROUND: Falls in older people represent a major age-related health challenge facing our society. Novel methods for delivery of falls prevention programs are required to increase effectiveness and adherence to these programs while containing costs. The primary aim of the Information and Communications Technology-based System to Predict and Prevent Falls (iStoppFalls) project was to develop innovative home-based technologies for continuous monitoring and exercise-based prevention of falls in community-dwelling older people. The aim of this paper is to describe the components of the iStoppFalls system. METHODS: The system comprised of 1) a TV, 2) a PC, 3) the Microsoft Kinect, 4) a wearable sensor and 5) an assessment and training software as the main components. RESULTS: The iStoppFalls system implements existing technologies to deliver a tailored home-based exercise and education program aimed at reducing fall risk in older people. A risk assessment tool was designed to identify fall risk factors. The content and progression rules of the iStoppFalls exergames were developed from evidence-based fall prevention interventions targeting muscle strength and balance in older people. CONCLUSIONS: The iStoppFalls fall prevention program, used in conjunction with the multifactorial fall risk assessment tool, aims to provide a comprehensive and individualised, yet novel fall risk assessment and prevention program that is feasible for widespread use to prevent falls and fall-related injuries. This work provides a new approach to engage older people in home-based exercise programs to complement or provide a potentially motivational alternative to traditional exercise to reduce the risk of falling.

Point of optimal kinematic error: improvement of the instantaneous helical pivot method for locating centers of rotation.

This paper proposes a variation of the instantaneous helical pivot technique for locating centers of rotation. The point of optimal kinematic error (POKE), which minimizes the velocity at the center of rotation, may be obtained by just adding a weighting factor equal to the square of angular velocity in Woltring׳s equation of the pivot of instantaneous helical axes (PIHA). Calculations are simplified with respect to the original method, since it is not necessary to make explicit calculations of the helical axis, and the effect of accidental errors is reduced. The improved performance of this method was validated by simulations based on a functional calibration task for the gleno-humeral joint center. Noisy data caused a systematic dislocation of the calculated center of rotation towards the center of the arm marker cluster. This error in PIHA could even exceed the effect of soft tissue artifacts associated to small and medium deformations, but it was successfully reduced by the POKE estimation.

Propagation of soft tissue artifacts to the center of rotation: a model for the correction of functional calibration techniques.

This paper presents a mathematical model for the propagation of errors in body segment kinematics to the location of the center of rotation. Three functional calibration techniques, usually employed for the gleno-humeral joint, are studied: the methods based on the pivot of the instantaneous helical axis (PIHA) or the finite helical axis (PFHA), and the "symmetrical center of rotation estimation" (SCoRE). A procedure for correcting the effect of soft tissue artifacts is also proposed, based on the equations of those techniques and a model of the artifact, like the one that can be obtained by double calibration. An experiment with a mechanical analog was performed to validate the procedure and compare the performance of each technique. The raw error (between 57 and 68mm) was reduced by a proportion of between 1:6 and less than 1:15, depending on the artifact model and the mathematical method. The best corrections were obtained by the SCoRE method. Some recommendations about the experimental setup for functional calibration techniques and the choice of a mathematical method are derived from theoretical considerations about the formulas and the results of the experiment.

Kinematic description of soft tissue artifacts: quantifying rigid versus deformation components and their relation with bone motion.

This paper proposes a kinematic approach for describing soft tissue artifacts (STA) in human movement analysis. Artifacts are represented as the field of relative displacements of markers with respect to the bone. This field has two components: deformation component (symmetric field) and rigid motion (skew-symmetric field). Only the skew-symmetric component propagates as an error to the joint variables, whereas the deformation component is filtered in the kinematic analysis process. Finally, a simple technique is proposed for analyzing the sources of variability to determine which part of the artifact may be modeled as an effect of the motion, and which part is due to other sources. This method has been applied to the analysis of the shank movement induced by vertical vibration in 10 subjects. The results show that the cluster deformation is very small with respect to the rigid component. Moreover, both components show a strong relationship with the movement of the tibia. These results suggest that artifacts can be modeled effectively as a systematic relative rigid movement of the marker cluster with respect to the underlying bone. This may be useful for assessing the potential effectiveness of the usual strategies for compensating for STA.

Representation of planar motion of complex joints by means of rolling pairs. Application to neck motion.

We propose to model planar movements between two human segments by means of rolling-without-slipping kinematic pairs. We compute the path traced by the instantaneous center of rotation (ICR) as seen from the proximal and distal segments, thus obtaining the fixed and moving centrodes, respectively. The joint motion is then represented by the rolling-without-slipping of one centrode on the other. The resulting joint kinematic model is based on the real movement and accounts for nonfixed axes of rotation; therefore it could improve current models based on revolute pairs in those cases where joint movement implies displacement of the ICR. Previous authors have used the ICR to characterize human joint motion, but they only considered the fixed centrode. Such an approach is not adequate for reproducing motion because the fixed centrode by itself does not convey information about body position. The combination of the fixed and moving centrodes gathers the kinematic information needed to reproduce the position and velocities of moving bodies. To illustrate our method, we applied it to the flexion-extension movement of the head relative to the thorax. The model provides a good estimation of motion both for position variables (mean R(pos)=0.995) and for velocities (mean R(vel)=0.958). This approach is more realistic than other models of neck motion based on revolute pairs, such as the dual-pivot model. The geometry of the centrodes can provide some information about the nature of the movement. For instance, the ascending and descending curves of the fixed centrode suggest a sequential movement of the cervical vertebrae.

Optimal average path of the instantaneous helical axis in planar motions with one functional degree of freedom.

This paper presents a model for determining the path of the instantaneous helical axis (IHA) that optimally represents human planar motions with one functional degree of freedom (fDOF). A human movement is said to have one fDOF when all degrees of freedom (DOFs) are coordinated such that all the kinematic variables can be expressed, across movement repetitions, as functions of only one independent DOF, except for a small natural intercycle variability quantified as lower than a prespecified value. The concept of fDOF allows taking into account that, due to motor coordination, human movements are executed in a repeatable manner. Our method uses the measurement of several repetitions of a given movement to obtain the optimal average IHA path. The starting point is a change of variables, from time to a joint position magnitude (generally an angle). In this way, instead of operating with the time-dependent single-valued trajectory of the successive cycles, our model permits the representation of any motion variable (e.g. positions and their time derivatives) as a cloud of points dependent on the joint angle. This allows the averaging to be performed over the displacements and their derivatives before determining the mean IHA path. We thus avoid the nonlinear magnification of errors and variability inherent in the IHA computation. Moreover, the IHA path can be considered as a geometric attribute of the joint and the type of motion, rather than of each single movement execution. An experiment was performed that show the accuracy and usefulness of the method.

Can human movement analysis contribute to usability understanding?

Nowadays human-machine interfaces are evaluated using different methodologies. These methodologies rarely consider the human movements involved in the interaction, and if so, the movements are considered in a simplistic manner. Another often neglected aspect is the relationship between the learning process and the use of the interface. Traditional approaches of cognitive modeling consider learning as just one continuous process. However there is some current evidence of concurrent processes on different time scales. This paper aims to answer, with experimental measurements, if learning actually implies a set of concurrent processes, if those processes are related to the coordinative aspects of hand movement, and how this can vary between young adult and elderly users. Two different interfaces, a washing machine and a domotic system, were analyzed with 23 and 20 people, respectively, classified as men or women and elderly (over 55) or adult (between 40 and 50). The results of the study provide support for the existence of different concurrent processes in learning, previously demonstrated for motor tasks. Moreover, the learning process is actually associated with changes in movement patterns. Finally, the results show that the progression of the learning process depends on age, although elderly people are equally capable of learning to use technological systems as young adults.