Recoil effect of the ice hockey stick during a slap shot

The purpose of this study was to examine the "recoil" effect of the ice hockey stick shaft during a stationary slap shot. Nine male adult subjects (four elite and five recreational) were tested. Their performances were evaluated by simultaneously recording stick movement and internal bending from high-speed digital video (1,000 Hz) and puck acceleration from a triaxial accelerometer positioned inside the puck. In addition, an electrical circuit measured blade-puck contact time. Data were analyzed with a one-way MANOVA for several dependent variables, including final puck velocity, puck acceleration, maximum stick shaft bending (angle and distance deflection), stick shaft angular velocities, blade-puck contact time, and corresponding time events. The results indicate the following. First, blade-puck contact time was greater for the elite than for recreational players (38 +/- 9 ms and 27 +/- 5 ms); however, measures for puck acceleration were essentially the same (63.8 g +/- 9.9 and 61.8 g +/- 19.5). Two, the elite players were able to generate greater puck velocities (120 +/- 18 km/h and 80.3 +/- 11.6 km/h). Three, the recoil timing was found to be reater for elite players (59.8% of blade-puck contact).     

Validation and Reliability of a Classification Method to Measure the Time Spent Performing Different Activities

The aim of this study was to validate the performance and reliability of results obtained from a classification model that measures time spent performing activities in confined (CE) and unrestricted (UE) environments. In CE, participants wore a pair of biaxial and/or triaxial accelerometers while performing pre-determined training activities classified as variants of lying down, dynamic standing, sitting, walking and running on two separate days. A classification model trained with activities performed in a specific order during the first day was developed to validate the activities performed in a random order on the second day (CE) and over 24 hours on a separate day (UE). The performance of the classification model was validated against triaxial accelerometers using six (x, y and step counts for arm and thigh) or eight (same as six features plus z axis) features. The reliability of the classification model was tested in both environments using six features. Results revealed an overall accuracy of 94% in CE and 90% in UE. The sensitivity in CE and UE was 94% and 95% for lying down, 88% and 80% for dynamic standing, 97% and 89% for sitting, 96% and 78% for walking and 90% and 64% for running, respectively. No significant differences were noted between performances obtained with six or eight features. Results were highly reproducible in both environments. The results obtained from the classification model were accurate and reproducible, and highlight the potential use of this approach in research to quantify the time spent performing different activities.     

A six degree of freedom head acceleration measurement device for use in football

The high incidence rate of concussions in football provides a unique opportunity to collect biomechanical data to characterize mild traumatic brain injury. The goal of this study was to validate a six degree of freedom (6DOF) measurement device with 12 single-axis accelerometers that uses a novel algorithm to compute linear and angular head accelerations for each axis of the head. The 6DOF device can be integrated into existing football helmets and is capable of wireless data transmission. A football helmet equipped with the 6DOF device was fitted to a Hybrid III head instrumented with a 9 accelerometer array. The helmet was impacted using a pneumatic linear impactor. Hybrid III head accelerations were compared with that of the 6DOF device. For all impacts, peak Hybrid III head accelerations ranged from 24 g to 176 g and 1,506 rad/s(2) to 14,431 rad/s(2). Average errors for peak linear and angular head acceleration were 1% ± 18% and 3% ± 24%, respectively. The average RMS error of the temporal response for each impact was 12.5 g and 907 rad/s(2).     

The accuracy of measuring the kinematics of rising from a chair with accelerometers and gyroscopes

The purpose of this study was to assess the accuracy of measuring angle and angular velocity of the upper body and upper leg during rising from a chair with accelerometers, using low-pass filtering of the accelerometer signal. Also, the improvement in accuracy of the measurement with additional use of high-pass filtered gyroscopes was assessed. Two uni-axial accelerometers and one gyroscope (DynaPort) per segment were used to measure angles and angular velocities of upper body and upper leg. Calculated angles and angular velocities were compared to a high-quality optical motion analysis system (Optotrak), using root mean squared error (RMS) and correlation coefficient (r) as parameters. The results for the sensors showed that two uni-axial accelerometers give a reasonable accurate measurement of the kinematics of rising from a chair (RMS = 2.9, 3.5, and 2.6 degrees for angle and RMS = 9.4, 18.4, and 11.5 degrees /s for angular velocity for thorax, pelvis, and upper leg, respectively). Additional use of gyroscopes improved the accuracy significantly (RMS = 0.8, 1.1, and 1.7 degrees for angle and RMS = 2.6, 4.0 and 4.9 degrees /s for angular velocity for thorax, pelvis and upper leg, respectively). The low-pass Butterworth filter had optimal cut-off frequencies of 1.05, 1.3, and 1.05 for thorax, pelvis, and upper leg, respectively. For the combined signal, the optimal cut-off frequencies were 0.18, 0.2, and 0,38 for thorax, pelvis and upper leg, respectively. The filters showed no subject specificity. This study provides an accurate, inexpensive and simple method to measure the kinematics of movements similar to rising from a chair.     

An algorithm for estimating acceleration magnitude and impact location using multiple nonorthogonal single-axis accelerometers

Accelerations of the head are the likely cause of concussion injury, but identifying the specific etiology of concussion has been difficult due to the lack of a valid animal or computer model. Contact sports, in which concussions are a rising health care concern, offer a unique research laboratory environment. However, measuring head acceleration in the field has many challenges including the need for large population sampling because of the relatively low incidence of concussions. We report a novel approach for calculating linear acceleration that can be incorporated into a head-mounted system for on-field use during contact sports. The advantages of this approach include the use of single-axis linear accelerometers, which reduce costs, and a nonorthogonal arrangement of the accelerometers, which simplifies the design criteria for a head-mounted and helmet compatible system. The purpose of this study was to describe the algorithm and evaluate its accuracy for measuring linear acceleration magnitude and impact location using computer simulation and experimental tests with various accelerometer configurations. A 10% error in magnitude and a 10 deg error in impact location were achieved using as few as six single-axis accelerometers mounted on a hemispherical headform.     

Brain-computer interface based on generation of visual images

This paper examines the task of recognizing EEG patterns that correspond to performing three mental tasks: relaxation and imagining of two types of pictures: faces and houses. The experiments were performed using two EEG headsets: BrainProducts ActiCap and Emotiv EPOC. The Emotiv headset becomes widely used in consumer BCI application allowing for conducting large-scale EEG experiments in the future. Since classification accuracy significantly exceeded the level of random classification during the first three days of the experiment with EPOC headset, a control experiment was performed on the fourth day using ActiCap. The control experiment has shown that utilization of high-quality research equipment can enhance classification accuracy (up to 68% in some subjects) and that the accuracy is independent of the presence of EEG artifacts related to blinking and eye movement. This study also shows that computationally-inexpensive bayesian classifier based on covariance matrix analysis yields similar classification accuracy in this problem as a more sophisticated Multi-class Common Spatial Patterns (MCSP) classifier.     

Validation of a wireless head acceleration measurement system for use in soccer play

Soccer heading has been studied previously with conflicting results. One major issue is the lack of knowledge regarding what actually occurs biomechanically during soccer heading impacts. The purpose of the current study is to validate a wireless head acceleration measurement system, head impact telemetry system (HITS) that can be used to collect head accelerations during soccer play. The HIT system was fitted to a Hybrid III (HIII) head form that was instrumented with a 3-2-2-2 accelerometer setup. Fifteen impact conditions were tested to simulate impacts commonly experienced during soccer play. Linear and angular acceleration were calculated for both systems and compared. Root mean square (RMS) error and cross correlations were also calculated and compared for both systems. Cross correlation values were very strong with r = .95 ± 0.02 for ball to head forehead impacts and r = .96 ± 0.02 for head to head forehead impacts. The systems showed a strong relationship when comparing RMS error, linear head acceleration, angular head acceleration, and the cross correlation values.     

Lightweight low-profile nine-accelerometer package to obtain head angular accelerations in short-duration impacts

Despite recognizing the importance of angular acceleration in brain injury, computations using data from experimental studies with biological models such as human cadavers have met with varying degrees of success. In this study, a lightweight and a low-profile version of the nine-accelerometer system was developed for applications in head injury evaluations and impact biomechanics tests. The triangular pyramidal nine-accelerometer package (PNAP) is precision-machined out of standard aluminum, is lightweight (65 g), and has a low profile (82 mm base width, 35 mm vertex height). The PNAP assures accurate orthogonal characteristics because all nine accelerometers are pre-aligned and attached before mounting on a human cadaver preparation. The feasibility of using the PNAP in human cadaver head studies is demonstrated by subjecting a specimen to an impact velocity of 8.1 m/s and the resultant angular acceleration peaked at 17 krad/s2. The accuracy and the high fidelity of the PNAP device at high and low angular acceleration levels were demonstrated by comparing the PNAP-derived angular acceleration data with separate tests using the internal nine-accelerometer head of the Hybrid III anthropomorphic test device. Mounting of the PNAP on a biological specimen such as a human cadaver head should yield very accurate angular acceleration data.     

An artificial neural network model of energy expenditure using nonintegrated acceleration signals.

Accelerometers are a promising tool for characterizing physical activity patterns in free living. The major limitation in their widespread use to date has been a lack of precision in estimating energy expenditure (EE), which may be attributed to the oversimplified time-integrated acceleration signals and subsequent use of linear regression models for EE estimation. In this study, we collected biaxial raw (32 Hz) acceleration signals at the hip to develop a relationship between acceleration and minute-to-minute EE in 102 healthy adults using EE data collected for nearly 24 h in a room calorimeter as the reference standard. From each 1 min of acceleration data, we extracted 10 signal characteristics (features) that we felt had the potential to characterize EE intensity. Using these data, we developed a feed-forward/back-propagation artificial neural network (ANN) model with one hidden layer (12 x 20 x 1 nodes). Results of the ANN were compared with estimations using the ActiGraph monitor, a uniaxial accelerometer, and the IDEEA monitor, an array of five accelerometers. After training and validation (leave-one-subject out) were completed, the ANN showed significantly reduced mean absolute errors (0.29 +/- 0.10 kcal/min), mean squared errors (0.23 +/- 0.14 kcal(2)/min(2)), and difference in total EE (21 +/- 115 kcal/day), compared with both the IDEEA (P < 0.01) and a regression model for the ActiGraph accelerometer (P < 0.001). Thus ANN combined with raw acceleration signals is a promising approach to link body accelerations to EE. Further validation is needed to understand the performance of the model for different physical activity types under free-living conditions.     

On the accuracy of the Head Impact Telemetry (HIT) System used in football helmets

On-field measurement of head impacts has relied on the Head Impact Telemetry (HIT) System, which uses helmet mounted accelerometers to determine linear and angular head accelerations. HIT is used in youth and collegiate football to assess the frequency and severity of helmet impacts. This paper evaluates the accuracy of HIT for individual head impacts. Most HIT validations used a medium helmet on a Hybrid III head. However, the appropriate helmet is large based on the Hybrid III head circumference (58 cm) and manufacturer's fitting instructions. An instrumented skull cap was used to measure the pressure between the head of football players (n=63) and their helmet. The average pressure with a large helmet on the Hybrid III was comparable to the average pressure from helmets used by players. A medium helmet on the Hybrid III produced average pressures greater than the 99th percentile volunteer pressure level. Linear impactor tests were conducted using a large and medium helmet on the Hybrid III. Testing was conducted by two independent laboratories. HIT data were compared to data from the Hybrid III equipped with a 3-2-2-2 accelerometer array. The absolute and root mean square error (RMSE) for HIT were computed for each impact (n=90). Fifty-five percent (n=49) had an absolute error greater than 15% while the RMSE was 59.1% for peak linear acceleration.     

BIOMECHANICS OF HEAD INJURY IN OLYMPIC TAEKWONDO AND BOXING

Objective

The purpose was to examine differences between taekwondo kicks and boxing punches in resultant linear head acceleration (RLA), head injury criterion (HIC15), peak head velocity, and peak foot and fist velocities. Data from two existing publications on boxing punches and taekwondo kicks were compared.

Methods

For taekwondo head impacts a Hybrid II Crash Dummy (Hybrid II) head was instrumented with a tri-axial accelerometer mounted inside the Hybrid II head. The Hybrid II was fixed to a height-adjustable frame and fitted with a protective taekwondo helmet. For boxing testing, a Hybrid III Crash Dummy head was instrumented with an array of tri-axial accelerometers mounted at the head centre of gravity.

Results

Differences in RLA between the roundhouse kick (130.11±51.67 g) and hook punch (71.23±32.19 g, d = 1.39) and in HIC15 (clench axe kick: 162.63±104.10; uppercut: 24.10±12.54, d = 2.29) were observed.

Conclusions

Taekwondo kicks demonstrated significantly larger magnitudes than boxing punches for both RLA and HIC.     

Measurement of six degrees of freedom head kinematics in impact conditions employing six accelerometers and three angular rate sensors (6aω configuration)

The ability to measure six degrees of freedom (6 DOF) head kinematics in motor vehicle crash conditions is important for assessing head-neck loads as well as brain injuries. A method for obtaining accurate 6 DOF head kinematics in short duration impact conditions is proposed and validated in this study. The proposed methodology utilizes six accelerometers and three angular rate sensors (6aω configuration) such that an algebraic equation is used to determine angular acceleration with respect to the body-fixed coordinate system, and angular velocity is measured directly rather than numerically integrating the angular acceleration. Head impact tests to validate the method were conducted using the internal nine accelerometer head of the Hybrid III dummy and the proposed 6aω scheme in both low (2.3?m/s) and high (4.0?m/s) speed impact conditions. The 6aω method was compared with a nine accelerometer array sensor package (NAP) as well as a configuration of three accelerometers and three angular rate sensors (3aω), both of which have been commonly used to measure 6 DOF kinematics of the head for assessment of brain and neck injuries. The ability of each of the three methods (6aω, 3aω, and NAP) to accurately measure 6 DOF head kinematics was quantified by calculating the normalized root mean squared deviation (NRMSD), which provides an average percent error over time. Results from the head impact tests indicate that the proposed 6aω scheme is capable of producing angular accelerations and linear accelerations transformed to a remote location that are comparable to that determined from the NAP scheme in both low and high speed impact conditions. The 3aω scheme was found to be unable to provide accurate angular accelerations or linear accelerations transformed to a remote location in the high speed head impact condition due to the required numerical differentiation. Both the 6aω and 3aω schemes were capable of measuring accurate angular displacement while the NAP instrumentation was unable to produce accurate angular displacement due to double numerical integration. The proposed 6aω scheme appears to be capable of measuring accurate 6 DOF kinematics of the head in any severity of impact conditions.     

Estimation of resistance exercise energy expenditure using triaxial accelerometry

Recently, it was demonstrated that a uniaxial accelerometer worn at the hip could estimate resistance exercise energy expenditure. As resistance exercise takes place in more than 1 plane, the use of a triaxial accelerometer may be more effective in estimating resistance exercise energy expenditure. The aims of this study were to estimate the energy cost of resistance exercise using triaxial accelerometry and to determine the optimal location for wearing triaxial accelerometers during resistance exercise. Thirty subjects (15 men and 15 women; age = 21.7 ± 1.0 years) performed a resistance exercise protocol consisting of 2 sets of 8 exercises (10RM loads). During the resistance exercise protocol, subjects wore triaxial accelerometers on the wrist, waist, and ankle; a heart rate monitor; and a portable metabolic system. Net energy expenditure was significantly correlated with vertical (r = 0.67, p < 0.001), horizontal (r = 0.43, p = 0.02), third axis (r = 0.36, p = 0.048), and sum of 3 axes (r = 0.50, p = 0.005) counts at the waist, and horizontal counts at the wrist (r = -0.40, p = 0.03). Regression analysis using fat-free mass, sex, and the sum of accelerometer counts at the waist as variables was used to develop an equation that explained 73% of the variance of resistance exercise energy expenditure. A triaxial accelerometer worn at the waist can be used to estimate resistance exercise energy expenditure but appears to offer no benefit over uniaxial accelerometry. The use of accelerometers in estimating resistance exercise energy expenditure may prove useful for individuals and athletes who participate in resistance training and are focused on maintaining a tightly regulated energy balance.     

Physical activity assessment with accelerometers: an evaluation against doubly labeled water

This review focuses on the ability of different accelerometers to assess daily physical activity as compared with the doubly labeled water (DLW) technique, which is considered the gold standard for measuring energy expenditure under free-living conditions. The PubMed Central database (U.S. NIH free digital archive of biomedical and life sciences journal literature) was searched using the following key words: doubly or double labeled or labeled water in combination with accelerometer, accelerometry, motion sensor, or activity monitor. In total, 41 articles were identified, and screening the articles' references resulted in one extra article. Of these, 28 contained sufficient and new data. Eight different accelerometers were identified: 3 uniaxial (the Lifecorder, the Caltrac, and the CSA/MTI/Actigraph), one biaxial (the Actiwatch AW16), 2 triaxial (the Tritrac-R3D and the Tracmor), one device based on two position sensors and two motion sensors (ActiReg), and the foot-ground contact pedometer. Many studies showed poor results. Only a few mentioned partial correlations for accelerometer counts or the increase in R(2) caused by the accelerometer. The correlation between the two methods was often driven by subject characteristics such as body weight. In addition, standard errors or limits of agreement were often large or not presented. The CSA/MTI/Actigraph and the Tracmor were the two most extensively validated accelerometers. The best results were found for the Tracmor; however, this accelerometer is not yet commercially available. Of those commercially available, only the CSA/MTI/Actigraph has been proven to correlate reasonably with DLW-derived energy expenditure.     

Rapid neck muscle adaptation alters the head kinematics of aware and unaware subjects undergoing multiple whiplash-like perturbations

To examine whether habituation confounds the study of whiplash injury using human subjects, we quantified changes in the magnitude and temporal development of the neck muscle electromyogram and peak linear and angular head/torso kinematics of subjects exposed to sequential whiplash-like perturbations. Forty-four seated subjects (23F, 21M) underwent 11 consecutive forward horizontal perturbations (peak sled acceleration=1.5 g). Electromyographic (EMG) activity was recorded over the sternocleidomastoid (SCM) and cervical paraspinal (PARA) muscles with surface electrodes, and head and torso kinematics were measured using linear and angular accelerometers and a 3D motion analysis system. EMG onset occurred at reflex latencies (67-75 ms in SCM) and did not vary with repeated perturbations. EMG amplitude was significantly attenuated by the second perturbation in PARA muscles and by the third perturbation in SCM muscles. The mean decrement in EMG amplitude between the first trial and the mean of the last five trials was between 41% and 64%. Related kinematic changes ranged from a 21% increase in head extension angle to a 29% decrease in forward acceleration at the forehead, and were also significantly different by the second exposure in some variables. Although a wider range of perturbation intensities and inter-perturbation intervals need to be studied, the significant changes observed in both muscle and kinematic variables by the second perturbation indicated that habituation was a potential confounder of whiplash injury studies using repeated perturbations of human subjects.     

Classification of broiler behaviours using triaxial accelerometer and machine learning

Understanding broiler behaviours provides important implications for animal well-being and farm management. The objectives of this study were to classify specific broiler behaviours by analysing data from wearable accelerometers using two machine learning models, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM). Lightweight triaxial accelerometers were used to record accelerations of nine 7-week-old broilers at a sampling frequency of 40 Hz. A total of 261.6-min data were labelled for four behaviours – walking, resting, feeding and drinking. Instantaneous motion features including magnitude area, vector magnitude, movement variation, energy, and entropy were extracted and stored in a dataset which was then segmented by one of the six window lengths (1, 3, 5, 7, 10 and 20 s) with 50% overlap between consecutive windows. The mean, variation, SD, minimum and maximum of each instantaneous motion feature and two-way correlations of acceleration data were calculated within each window, yielding a total of 43 statistic features for training and testing of machine learning models. Performance of the models was evaluated using pure behaviour datasets (single behaviour type per dataset) and continuous behaviour datasets (continuous recording that involved multiple behaviour types per dataset). For pure behaviour datasets, both KNN and SVM models showed high sensitivities in classifying broiler resting (87% and 85%, respectively) and walking (99% and 99%, respectively). The accuracies of SVM were higher than KNN in differentiating feeding (88% and 75%, respectively) and drinking (83% and 62%, respectively) behaviours. Sliding window with 1-s length yielded the best performance for classifying continuous behaviour datasets. The performance of classification model generally improved as more birds were included for training. In conclusion, classification of specific broiler behaviours can be achieved by recording bird triaxial accelerations and analysing acceleration data through machine learning. Performances of different machine learning models differ in classifying specific broiler behaviours.     

Direct conversion of xylan to ethanol by recombinant Saccharomyces cerevisiae strains displaying an engineered minihemicellulosome

Arabinoxylan is a heteropolymeric chain of a β-1,4-linked xylose backbone substituted with arabinose residues, representing a principal component of plant cell walls. Here we developed recombinant Saccharomyces cerevisiae strains as whole-cell biocatalysts capable of combining hemicellulase production, xylan hydrolysis, and hydrolysate fermentation into a single step. These strains displayed a series of uni-, bi-, and trifunctional minihemicellulosomes that consisted of a miniscaffoldin (CipA3/CipA1) and up to three chimeric enzymes. The miniscaffoldin derived from Clostridium thermocellum contained one or three cohesin modules and was tethered to the cell surface through the S. cerevisiae a-agglutinin adhesion receptor. Up to three types of hemicellulases, an endoxylanase (XynII), an arabinofuranosidase (AbfB), and a β-xylosidase (XlnD), each bearing a C-terminal dockerin, were assembled onto the miniscaffoldin by high-affinity cohesin-dockerin interactions. Compared to uni- and bifunctional minihemicellulosomes, the resulting quaternary trifunctional complexes exhibited an enhanced rate of hydrolysis of arabinoxylan. Furthermore, with an integrated d-xylose-utilizing pathway, the recombinant yeast displaying the bifunctional minihemicellulosome CipA3-XynII-XlnD could simultaneously hydrolyze and ferment birchwood xylan to ethanol with a yield of 0.31 g per g of sugar consumed.     

Verification of biomechanical methods employed in a comprehensive study of mild traumatic brain injury and the effectiveness of American football helmets

Concussion, or mild traumatic brain injury, occurs in many activities, mostly as a result of the head being accelerated. A comprehensive study has been conducted to understand better the mechanics of the impacts associated with concussion in American football. This study involves a sequence of techniques to analyse and reconstruct many different head impact scenarios. It is important to understand the validity and accuracy of these techniques in order to be able to use the results of the study to improve helmets and helmet standards. Two major categories of potential errors have been investigated. The first category concerns error sources specific to the use of crash test dummy instrumentation (accelerometers) and associated data processing techniques. These are relied upon to establish both linear and angular head acceleration responses. The second category concerns the use of broadcast video data and crash test dummy head-neck-torso systems. These are used to replicate the complex head impact scenarios of whole body collisions that occur on the football field between two living human beings. All acceleration measurement and processing techniques were based on well-established practices and standards. These proved to be reliable and reproducible. Potential errors in the linear accelerations due to electrical or mechanical noise did not exceed 2% for the three different noise sources investigated. Potential errors in the angular accelerations due to noise could be as high as 6.7%, due to error accumulation of multiple linear acceleration measurements. The potential error in the relative impact velocity between colliding heads could be as high as 11%, and was found to be the largest error source in the sequence of techniques to reconstruct the game impacts. Full-scale experiments with complete crash test dummies in staged head impacts showed maximum errors of 17% for resultant linear accelerations and 25% for resultant angular accelerations.     

Validation of a noninvasive system for measuring head acceleration for use during boxing competition

Although the epidemiology and mechanics of concussion in sports have been investigated for many years, the biomechanical factors that contribute to mild traumatic brain injury remain unclear because of the difficulties in measuring impact events in the field. The purpose of this study was to validate an instrumented boxing headgear (IBH) that can be used to measure impact severity and location during play. The instrumented boxing headgear data were processed to determine linear and rotational acceleration at the head center of gravity, impact location, and impact severity metrics, such as the Head Injury Criterion (HIC) and Gadd Severity Index (GSI). The instrumented boxing headgear was fitted to a Hybrid III (HIII) head form and impacted with a weighted pendulum to characterize accuracy and repeatability. Fifty-six impacts over 3 speeds and 5 locations were used to simulate blows most commonly observed in boxing. A high correlation between the HIII and instrumented boxing headgear was established for peak linear and rotational acceleration (r2= 0.91), HIC (r2 = 0.88), and GSI (r2 = 0.89). Mean location error was 9.7 +/- 5.2 masculine. Based on this study, the IBH is a valid system for measuring head acceleration and impact location that can be integrated into training and competition.     

Assessment of inertial and gravitational inputs to the vestibular system

A new device for the assessment of instantaneous angular and linear accelerations of the head is presented, which is based on four linear tri-axial accelerometers suitably attached to the head by an helmet. A procedure for reproducible helmet placement and calibration is given. A method is also illustrated to work out the different linear accelerations sensed by the vestibular organs in the left and right labyrinths and the components of the angular acceleration sensed by their semicircular canals. The computation is based on few individual parameters describing the helmet position with respect to external landmarks and on the average internal position and orientation of the vestibula. The purpose is to study the components of internal inertial forces, which represent the primary inputs to the vestibular system devoted to equilibrium and oculomotor control. The system is designed to be of easy application during rehabilitation exercises and in clinical environment during diagnostic and therapeutic manoeuvres. The prototype is tested with simple free movements such as "yes", "no", and gait.