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Taborri J.,University of Rome La Sapienza | Rossi S.,University of Tuscia | Palermo E.,University of Rome La Sapienza | Patane F.,Niccolo Cusano University | And 2 more authors.
Sensors (Switzerland) | Year: 2014

In this work, we decided to apply a hierarchical weighted decision, proposed and used in other research fields, for the recognition of gait phases. The developed and validated novel distributed classifier is based on hierarchical weighted decision from outputs of scalar Hidden Markov Models (HMM) applied to angular velocities of foot, shank, and thigh. The angular velocities of ten healthy subjects were acquired via three uni-axial gyroscopes embedded in inertial measurement units (IMUs) during one walking task, repeated three times, on a treadmill. After validating the novel distributed classifier and scalar and vectorial classifiers-already proposed in the literature, with a cross-validation, classifiers were compared for sensitivity, specificity, and computational load for all combinations of the three targeted anatomical segments. Moreover, the performance of the novel distributed classifier in the estimation of gait variability in terms of mean time and coefficient of variation was evaluated. The highest values of specificity and sensitivity (>0.98) for the three classifiers examined here were obtained when the angular velocity of the foot was processed. Distributed and vectorial classifiers reached acceptable values (>0.95) when the angular velocity of shank and thigh were analyzed. Distributed and scalar classifiers showed values of computational load about 100 times lower than the one obtained with the vectorial classifier. In addition, distributed classifiers showed an excellent reliability for the evaluation of mean time and a good/excellent reliability for the coefficient of variation. In conclusion, due to the better performance and the small value of computational load, the here proposed novel distributed classifier can be implemented in the real-time application of gait phases recognition, such as to evaluate gait variability in patients or to control active orthoses for the recovery of mobility of lower limb joints. © 2014 by the authors; licensee MDPI, Basel, Switzerland. Source


Ancillao A.,University of Rome La Sapienza | Rossi S.,University of Tuscia | Patane F.,Niccolo Cusano University | Cappa P.,University of Rome La Sapienza | Cappa P.,Movement Analysis and Robotics Laboratory
2015 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2015 - Proceedings | Year: 2015

Strength measurements are popular in the clinical practice to evaluate the health status of patients and quantify the outcome of training programs. Currently a common method to measure strength is based on Hand Held Dynamometers (HHD) which is operator-dependent. Some studies were conducted on repeatability of strength measurements but they were limited to the statistical analysis of repeated measurements of force. In this work, the authors developed a methodology to study the quality of knee flexion/extension strength measurements by measuring the effective HHD position and orientation with respect to the patient. HHD positioning attitude was measured by means of an Optoelectronic System for which a marker protocol was defined ad-hoc. The approach allowed to assess quality of measurements and operator's ability by means of quantitative indices. The protocol permitted the evaluation of: angles of HHD application, angular range of motion of the knee and range of motion of the HHD. RMSE parameters allowed to quantify the inaccuracy associated to the selected indices. Results showed that the operator was not able to keep the subject's limb completely still. The force exerted by the subject was higher in knee extension and the knee range of motion was higher than expected, however the operator had more difficulties in holding the HHD in knee flexion trials. This work showed that HHD positioning should be as accurate as possible, as it plays an important role for the strength evaluation. Moreover, the operator should be properly trained and should be strong enough to counteract the force of the subject. © 2015 IEEE. Source


Taborri J.,University of Rome La Sapienza | Palermo E.,University of Rome La Sapienza | Rossi S.,University of Tuscia | Cappa P.,University of Rome La Sapienza | Cappa P.,Movement Analysis and Robotics Laboratory
Sensors (Switzerland) | Year: 2016

In the last years, gait phase partitioning has come to be a challenging research topic due to its impact on several applications related to gait technologies. A variety of sensors can be used to feed algorithms for gait phase partitioning, mainly classifiable as wearable or non-wearable. Among wearable sensors, footswitches or foot pressure insoles are generally considered as the gold standard; however, to overcome some inherent limitations of the former, inertial measurement units have become popular in recent decades. Valuable results have been achieved also though electromyography, electroneurography, and ultrasonic sensors. Non-wearable sensors, such as opto-electronic systems along with force platforms, remain the most accurate system to perform gait analysis in an indoor environment. In the present paper we identify, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution. Finally, we comparatively examine the obtainable gait phase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments. © 2016 by the authors; licensee MDPI, Basel, Switzerland. Source


Pacilli A.,University of Rome La Sapienza | Pacilli A.,Movement Analysis and Robotics Laboratory | Germanotta M.,University of Rome La Sapienza | Germanotta M.,Movement Analysis and Robotics Laboratory | And 4 more authors.
Applied Bionics and Biomechanics | Year: 2014

BACKGROUND: Although robotic therapy is at the forefront of upper limb rehabilitation, there is limited information about the importance of selecting age-matched subjects to evaluate recovery of arm movement during rehabilitation.OBJECTIVE: This study aims to quantify differences in the arm motion of healthy children and adults when they interact with a planar robot, in order to determine whether an age-matched control group is necessary in clinical studies involving pediatric patients.METHODS: Ten children (aged 7 to 10 years) and ten adults (aged 23 to 25 years) performed, at self-selected speed and accuracy, planar-reaching and circle-drawing movements with a robotic device. We analyzed the motor performances for the two groups quantifying the participants' dexterity in completing two chosen tasks. The measurement of the entire upper limb was obtained by merging the data provided by the robot with that of an optical tracking system.RESULTS: Children drew circles with less smoothness than adults but with the same accuracy and joint coordination. During planar reaching task, children optimized only the coordination but performed the movement with less accuracy and smoothness than adults.CONCLUSIONS: Our findings provide evidence that age-matched healthy children should be used to quantify the recovery of robot-mediated therapy in children with upper limb impairments. © 2014-IOS Press and the authors. All rights reserved. Source


Cappa P.,University of Rome La Sapienza | Cappa P.,Movement Analysis and Robotics Laboratory | Jackson J.L.,Movement Analysis and Robotics Laboratory | Jackson J.L.,University of Rome La Sapienza | And 2 more authors.
IEEE Transactions on Biomedical Engineering | Year: 2010

This paper characterizes the moment measurement accuracy for a novel parallel spherical robot (SR) for dynamic posturography, controllable by position or impedance. The SR consists of three linearmotors placed on a support base, amoving base, and three passive arms equipped with uniaxial load cells permitting impedance controlled perturbations. To evaluate the accuracy, a subject stood still on the SR, set in position control mode, while selected sinusoidal trajectories were applied. The moments computed by the load cells were compared to the value measured by a six-component force platform, placed on top of the rotating base. For the intended application of the SR, the errors were negligible with the worse case of only 4 Nm in a total of 15 trials (five conditions, three repetitions). The observed moment error was relatedmainly to the intrinsic accuracy of the sensors, equal to about 7 N. To demonstrate clinical applicability, the platform was set to impedance control mode and a protocol was tested with a 12-yearold girl with brain injury and a group of four healthy subjects. In total, 24 trials (eight conditions, three repetitions) were recorded for each subject. The results of this pilot study identified distinctive postural behaviors and therefore showed that the SR can be considered as an effective tool for dynamic posturography. © 2006 IEEE. Source

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