Velio Macellari

The development and test of a device for the reconstruction of 3-D position and orientation by means of a kinematic sensor assembly with rate gyroscopes and accelerometers

In this paper, we propose a device for the Position and Orientation (P&O) reconstruction of human segmental locomotion tasks. It is based on three mono-axial accelerometers and three angular velocity sensors, geometrically arranged to form two orthogonal terns. The device was bench tested using step-by-step motor-based equipment. The characteristics of the six channels under bench test conditions were: crosstalk absent, non linearity </spl plusmn/0, 1% fs, hysteresis <0, 1% fs, accuracy 0, 3% fs, overall resolution better than 0, 04 deg/s, 2*g*10/sup -4/. The device was validated with the stereophotogrammetric body motion analyzer during the execution of three different locomotion tasks: stand-to-sit, sit-to-stand, gait-initiation. Results obtained comparing the trajectories of the two methods showed that the errors were lower than 3*10/sup -2/ m and 2 deg during a 4s of acquisition and lower than 6*10/sup -3/ m and 0.2 deg during the effective duration of a locomotory task; showing that the wearable device hereby presented permits the 3-D reconstruction of the movement of the body segment to which it is affixed for time-limited clinical applications.

Audio-biofeedback for balance improvement: an accelerometry-based system

This paper introduces a prototype audio-biofeedback system for balance improvement through the sonification using trunk kinematic information. In tests of this system, normal healthy subjects performed several trials in which they stood quietly in three sensory conditions while wearing an accelerometric sensory unit and headphones. The audio-biofeedback system converted in real-time the two-dimensional horizontal trunk accelerations into a stereo sound by modulating its frequency, level, and left/right balance. Preliminary results showed that subjects improved balance using this audio-biofeedback system and that this improvement was greater the more that balance was challenged by absent or unreliable sensory cues. In addition, high correlations were found between the center of pressure displacement and trunk acceleration, suggesting accelerometers may be useful for quantifying standing balance.

Is it feasible to reconstruct body segment 3-D position and orientation using accelerometric data?

The analysis of the mechanics of the musculo-skeletal system during the execution of a motor task requires the determination of the instantaneous position and orientation of the body segments involved in relation to an inertial system of reference. By using adequately assembled uniaxial accelerometric sensors, an easy-to-manage measurement system can be obtained that estimates the three-dimensional position and orientation (P&O) of a body segment through an appropriate analytical model. However, the extent to which experimental errors, in particular accelerometers (ACs) assembly inaccuracies, affect such estimation has never been systematically investigated. This paper systematically analyzes the sensitivity of analytical models of body segment P&O reconstruction through a six-AC system and a nine-AC system to different sources of experimental error. We simulated and statistically assessed the performance of these models in the case of body segment motions typical of movements under muscular control. The results obtained indicated that the inaccuracy in the orientation of the individual ACs active axes and the offset error in the AC responses were the major sources of P&O estimation errors. In particular, no accurate estimation of position was possible with the analytical models analyzed. Under the motion conditions simulated in this study, no substantial advantages were found in using a nine-AC system rather than a six-AC system. Considering that the magnitudes of the simulated experimental errors were quite low (/spl les/0.1 deg: ACs orientation; /spl les/10/sup -4/ m: uncertainty of the distance between two ACs; /spl les/10/sup -2/ ms/sup -2/: random error; 0.5/spl middot/10/sup -2/ ms/sup -2/: offset error), the results indicate that none of the two ACs systems analyzed is suitable for body segment P&O estimation in routine biomechanical applications.

Community-Based Adaptive Physical Activity Program for Chronic Stroke: Feasibility, Safety, and Efficacy of the Empoli Model

Objective. To determine whether Adaptive Physical Activity (APA-stroke), a community-based exercise program for participants with hemiparetic stroke, improves function in the community. Methods. Nonrandomized controlled study in Tuscany, Italy, of participants with mild to moderate hemiparesis at least 9 months after stroke. Forty-nine participants in a geographic health authority (Empoli) were offered APA-stroke (40 completed the study). Forty-four control participants in neighboring health authorities (Florence and Pisa) received usual care (38 completed the study). The APA intervention was a community-based progressive group exercise regimen that included walking, strength, and balance training for 1 hour, thrice a week, in local gyms, supervised by gym instructors. No serious adverse clinical events occurred during the exercise intervention. Outcome measures included the following: 6-month change in gait velocity (6-Minute Timed Walk), Short Physical Performance Battery (SPPB), Berg Balance Scale, Stroke Impact Scale (SIS), Barthel Index, Hamilton Rating Scale for Depression, and Index of Caregivers Strain. Results. After 6 months, the intervention group improved whereas controls declined in gait velocity, balance, SPPB, and SIS social participation domains. These between-group comparisons were statistically significant at P < .00015. Individuals with depressive symptoms at baseline improved whereas controls were unchanged (P < .003). Oral glucose tolerance tests were performed on a subset of participants in the intervention group. For these individuals, insulin secretion declined 29% after 6 months (P = .01). Conclusion. APA-stroke appears to be safe, feasible, and efficacious in a community setting.

WARD: a pneumatic system for body weight relief in gait rehabilitation

The paper presents Walking Assistance and Rehabilitation Device (WARD), a system for walking rehabilitation devised to relieve the patient of his/her body weight of a constant and prescribed amount by externally supporting the subject at the upper trunk and pelvis level by means of a harness. The system is based on a pneumatic actuator that has proved to be effective at maintaining a constant relief force. The constancy of this force that should be maintained even under high body weight support (BWS) conditions (70-80% of body weight) seems to be important for a correct motor pattern. A law has been identified that may be useful to adjust walking speed as a function of the prescribed BWS. WARD is simple to construct, practical to use, and has been characterized on healthy subjects.

Integrated pressure-force-kinematics measuring system for the characterisation of plantar foot loading during locomotion

Plantar pressure, ground reaction force and body-segment kinematics measurements are largely used in gait analysis to characterise normal and abnormal function of the human foot. The combination of all these data together provides a more exhaustive, detailed and accurate view of foot loading during activities than traditional measurement systems alone do. A prototype system is presented that integrates a pressure platform, a force platform and a 3D anatomical tracking system to acquire combined information about foot function and loading. A stereophotogrammetric system and an anatomically based protocol for foot segment kinematics is included in a previously devised piezo-dynamometric system that combines pressure and force measurements. Experimental validation tests are carried out to check for both spatial and time synchronisation. Misalignment of the three systems is found to be within 6.0, 5.0 and 1.5mm for the stereophotogrammetric system, force platform and pressure platform, respectively. The combination of position and pressure data allows for a more accurate selection of plantar foot subareas on the footprint. Measurements are also taken on five healthy volunteers during level walking to verify the feasibility of the overall experimental protocol. Four main subareas are defined and identified, and the relevant vertical and shear force data are computed. The integrated system is effective when there is a need for loading measurements in specific plantar foot subareas. This is attractive both in clinical assessment and in biomechanics research.

Two-thirds power law in human locomotion: role of ground contact forces.

Are there general rules for the generation of curvilinear motion of the end-effector? Form and kinematics of the arm trajectory are typically inter-related. A relationship between velocity and curvature of the endpoint path has been previously described and quantified as the two-thirds power law. Here we show that the two-thirds power law holds also for the foot trajectory (during the swing phase) in human locomotion for a wide range of walking speeds and gravitational loads, but air-stepping. In air-stepping, it was violated systematically. The results suggest that the power law represents a general constrain of biological motion, may be attributed to both mechanical and neural factors and can depend on natural interactions with external environment.

CoSTEL: a computer peripheral remote sensing device for 3-dimensional monitoring of human motion.

An automatic system (CoSTEL) which permits the reconstruction of the instantaneous 3-dimensional position of target points (infra-red light emitting body markers) in a laboratory frame was designed. The 3-dimensional CoSTEL transducer is based on a suitable spatial arrangement of three one-dimensional transducers. Each transducer is made of a charge-coupled device linear array image sensor lying on the focal plane of a toroidal lens and appropriately aligned with it. The system was conceived for 3-dimensional whole body movement analysis and is able to track eight landmarks per subject side simultaneously. Its basic features are resolution of 1/4000, maximum sampling frequency 1·1 kHz (100 Hz is actually used), large insensitivity to background light and transducer output in digital form. These features provide a high level of accuracy, reliability and working stability.

Telemonitoring and Telerehabilitation of Patients with Parkinson’s Disease: Health Technology Assessment of a Novel Wearable Step Counter

Step counting is an important index of motion in telemonitoring. One of the most diffused wearable systems, designed for this purpose, is the pedometer. The accuracy of commercial pedometers has been reported in the literature. Several limits have been found in many commercial systems both in healthy subjects and in people with disabilities. Furthermore, commercial pedometers lack interoperability. This paper introduces a new wearable system for step counting for telemonitoring applications. This system is based on a wearable device with a force-sensing resistor. It is affixed on the gastrocnemius muscle for monitoring muscular expansion correlated with the gait. The data exchange is assured by the XTR-434H (Aurel, FC, Italy) telemetric system. The proposed gastrocnemius expansion measurement unit (GEMU) was tested on 5 subjects with Parkinsons disease at Level 3 of the Tinetti test of unbalance. Ten repetitions of 500 steps with three different speeds (fast, slow, and normal) were performed. The mean error was <0.5%. Results also showed that GEMU performed better than an accelerometer unit (considered in the literature the best solution for this disability). The study showed that GEMU had a high performance in subjects with Parkinsons disease, causing a high degree of unbalance that confounded motion style. The next phase will be the optimization of GEMU for long-term medical applications at the patients home.

New neural network classifier of fall-risk based on the Mahalanobis distance and kinematic parameters assessed by a wearable device

Fall prevention lacks easy, quantitative and wearable methods for the classification of fall-risk (FR). Efforts must be thus devoted to the choice of an ad hoc classifier both to reduce the size of the sample used to train the classifier and to improve performances. A new methodology that uses a neural network (NN) and a wearable device are hereby proposed for this purpose. The NN uses kinematic parameters assessed by a wearable device with accelerometers and rate gyroscopes during a posturography protocol. The training of the NN was based on the Mahalanobis distance and was carried out on two groups of 30 elderly subjects with varying fall-risk Tinetti scores. The validation was done on two groups of 100 subjects with different fall-risk Tinetti scores and showed that, both in terms of specificity and sensitivity, the NN performed better than other classifiers (naive Bayes, Bayes net, multilayer perceptron, support vector machines, statistical classifiers). In particular, (i) the proposed NN methodology improved the specificity and sensitivity by a mean of 3% when compared to the statistical classifier based on the Mahalanobis distance (SCMD) described in Giansanti (2006 Physiol. Meas. 27 1081-90); (ii) the assessed specificity was 97%, the assessed sensitivity was 98% and the area under receiver operator characteristics was 0.965.