Paolo Cappa | Università degli Studi "La Sapienza" di Roma (original) (raw)
Papers by Paolo Cappa
Gait & Posture, 2009
vertebra. The horizontal translation of the head as well as its inclination angles were computed ... more vertebra. The horizontal translation of the head as well as its inclination angles were computed during four consecutive trials, lasting 5 min each, in the following conditions: (a) no load applied, (b) wearing the loading cap, (c) wearing the cap after walking for 5 min, and (d) no weight applied after having had the loading cap applied for 15 min. Differences relatively to the initial, unloaded head position were evaluated.
PLOS ONE, 2016
The available clinical outcome measures of disability in multiple sclerosis are not adequately re... more The available clinical outcome measures of disability in multiple sclerosis are not adequately responsive or sensitive. To investigate the feasibility of inertial sensor-based gait analysis in multiple sclerosis. A cross-sectional study of 80 multiple sclerosis patients and 50 healthy controls was performed. Lower-limb kinematics was evaluated by using a commercially available magnetic inertial measurement unit system. Mean and standard deviation of range of motion (mROM, sROM) for each joint of lower limbs were calculated in one minute walking test. A motor performance index (E) defined as the sum of sROMs was proposed. We established two novel observer-independent measures of disability. Hip mROM was extremely sensitive in measuring lower limb motor impairment, being correlated with muscle strength and also altered in patients without clinically detectable disability. On the other hand, E index discriminated patients according to disability, being altered only in patients with moderate and severe disability, regardless of walking speed. It was strongly correlated with fatigue and patient-perceived health status. Inertial sensor-based gait analysis is feasible and can detect clinical and subclinical disability in multiple sclerosis.
Journal of NeuroEngineering and Rehabilitation, 2015
Background: Friedreich's ataxia (FRDA) is the most common hereditary autosomal recessive form of ... more Background: Friedreich's ataxia (FRDA) is the most common hereditary autosomal recessive form of ataxia. In this disease there is early manifestation of gait ataxia, and dysmetria of the arms and legs which causes impairment in daily activities that require fine manual dexterity. To date there is no cure for this disease. Some novel therapeutic approaches are ongoing in different steps of clinical trial. Development of sensitive outcome measures is crucial to prove therapeutic effectiveness. The aim of the study was to assess the reliability and sensitivity of quantitative and objective assessment of upper limb performance computed by means of the robotic device and to evaluate the correlation with clinical and functional markers of the disease severity.
Physiological Measurement, 2014
Magnetic inertial measurement unit systems (MIMU) offer the potential to perform joint kinematics... more Magnetic inertial measurement unit systems (MIMU) offer the potential to perform joint kinematics evaluation as an alternative to optoelectronic systems (OS). Several studies have reported the effect of indoor magnetic field disturbances on the MIMU's heading output, even though the overall effect on the evaluation of lower limb joint kinematics is not yet fully explored. The aim of the study is to assess the influence of indoor magnetic field distortion on gait analysis trials conducted with a commercial MIMU system. A healthy adult performed gait analysis sessions both indoors and outdoors. Data collected indoors were post-processed with and without a heading correction methodology performed with OS at the start of the gait trial. The performance of the MIMU system is characterized in terms of indices, based on the mean value of lower limb joint angles and the associated ROM, quantifying the system repeatability. We find that the effects of magnetic field distortion, such as the one we experienced in our lab, were limited to the transverse plane of each joint and to the frontal plane of the ankle. Sagittal plane values, instead, showed sufficient repeatability moving from outdoors to indoors. Our findings provide indications to clinicians on MIMU performance in the measurement of lower limb kinematics.
Sensors, 2014
In this work, we decided to apply a hierarchical weighted decision, proposed and used in other re... more 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 OPEN ACCESS Sensors 2014, 14 16213
Proceedings of 2nd International Electronic Conference on Sensors and Applications, 2015
Gait & Posture, 2009
Abstracts / Gait & Posture 30S (2009) S1-S153 models. We would, however, be tentative in using th... more Abstracts / Gait & Posture 30S (2009) S1-S153 models. We would, however, be tentative in using this system for faster movement speeds, at present.
Measurement, 2014
ABSTRACT This paper describes a novel functional body-to-sensor calibration procedure for inertia... more ABSTRACT This paper describes a novel functional body-to-sensor calibration procedure for inertial sensor-based gait analysis. The procedure is designed to be easily and autonomously performable by the subject, without the need for precise sensor positioning, or the performance of specific movements. The procedure consists in measuring the vertical axis during two static positions, and is not affected by magnetic field distortion. The procedure has been validated on ten healthy subjects using an optoelectronic system to measure the actual body-to-sensor rotation matrices. The effects of different sensor positions on each body segment, or different levels of subject inclination during the second static position of the procedure, resulted unnoticeable. The procedure showed accuracy and repeatability values less than 4° for each angle except for the ankle int–external rotation (9.7°, 7.2°). The results demonstrate the validity of the procedure, since they are comparable with those reported for the most-adopted protocols in gait analysis.
Gait & Posture, 2011
Abstracts / Gait & Posture 33S (2011) S1-S66 S13 the SMWT. Better performance was also noted in t... more Abstracts / Gait & Posture 33S (2011) S1-S66 S13 the SMWT. Better performance was also noted in the TUG and BBT scores in the RAGT group. Subjects also reported a reduced motor fatigue after training.
PLoS ONE, 2013
In this work, we develop a novel gait phase detection algorithm based on a hidden Markov model, w... more In this work, we develop a novel gait phase detection algorithm based on a hidden Markov model, which uses data from foot-mounted single-axis gyroscopes as input. We explore whether the proposed gait detection algorithm can generate equivalent results as a reference signal provided by force sensitive resistors (FSRs) for typically developing children (TD) and children with hemiplegia (HC). We find that the algorithm faithfully reproduces reference results in terms of high values of sensitivity and specificity with respect to FSR signals. In addition, the algorithm distinguishes between TD and HC and is able to assess the level of gait ability in patients. Finally, we show that the algorithm can be adapted to enable real-time processing with high accuracy. Due to the small, inexpensive nature of gyroscopes utilized in this study and the ease of implementation of the developed algorithm, this work finds application in the on-going development of active orthoses designed for therapy and locomotion in children with gait pathologies.
Sensors, 2015
Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for l... more Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for lower limbs. Hidden Markov Models (HMMs) represent a viable solution, but they need subject-specific training, making data processing very time-consuming. Here, we validated an inter-subject procedure to avoid the intra-subject one in two, four and six gait-phase models in pediatric subjects. The inter-subject procedure consists in the identification of a standardized parameter set to adapt the model to measurements. We tested the inter-subject procedure both on scalar and distributed classifiers. Ten healthy children and ten hemiplegic children, each equipped with two Inertial Measurement Units placed on shank and foot, were recruited. The sagittal component of angular velocity was recorded by gyroscopes while subjects performed four walking trials on a treadmill. The goodness of classifiers was evaluated with the Receiver Operating Characteristic. The results provided a goodness from good to optimum for all examined classifiers (0 < G < 0.6), with the best performance for the distributed classifier in two-phase recognition (G = 0.02). Differences
Sensors (Basel, Switzerland), 2016
In the last years, gait phase partitioning has come to be a challenging research topic due to its... more 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 ex...
2015 IEEE International Conference on Rehabilitation Robotics (ICORR), 2015
2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings, 2015
In this paper we present and validate a methodology to avoid the training procedure of a classifi... more In this paper we present and validate a methodology to avoid the training procedure of a classifier based on an Hidden Markov Model (HMM) for a real-time gait recognition of two or four phases, implemented to control pediatric active orthoses of lower limb. The new methodology consists in the identification of a set of standardized parameters, obtained by a data set of angular velocities of healthy subjects age-matched. Sagittal angular velocities of lower limbs of ten typically developed children (TD) and ten children with hemiplegia (HC) were acquired by means of the tri-axial gyroscope embedded into Magnetic Inertial Measurement Units (MIMU). The actual sequence of gait phases was captured through a set of four foot switches. The experimental protocol consists in two walking tasks on a treadmill set at 1.0 and 1.5 km/h. We used the Goodness (G) as parameter, computed from Receiver Operating Characteristic (ROC) space, to compare the results obtained by the new methodology with the ones obtained by the subject-specific training of HMM via the Baum-Welch Algorithm. Paired-sample t-tests have shown no significant statistically differences between the two procedures when the gait phase detection was performed with the gyroscopes placed on the foot. Conversely, significant differences were found in data gathered by means of gyroscopes placed on shank. Actually, data relative to both groups presented G values in the range of good/optimum classifier (i.e. G ≤ 0.3), with better performance for the two-phase classifier model. In conclusion, the novel methodology here proposed guarantees the possibility to omit the off-line subject-specific training procedure for gait phase detection and it can be easily implemented in the control algorithm of active orthoses.
Gait & Posture, 2009
vertebra. The horizontal translation of the head as well as its inclination angles were computed ... more vertebra. The horizontal translation of the head as well as its inclination angles were computed during four consecutive trials, lasting 5 min each, in the following conditions: (a) no load applied, (b) wearing the loading cap, (c) wearing the cap after walking for 5 min, and (d) no weight applied after having had the loading cap applied for 15 min. Differences relatively to the initial, unloaded head position were evaluated.
PLOS ONE, 2016
The available clinical outcome measures of disability in multiple sclerosis are not adequately re... more The available clinical outcome measures of disability in multiple sclerosis are not adequately responsive or sensitive. To investigate the feasibility of inertial sensor-based gait analysis in multiple sclerosis. A cross-sectional study of 80 multiple sclerosis patients and 50 healthy controls was performed. Lower-limb kinematics was evaluated by using a commercially available magnetic inertial measurement unit system. Mean and standard deviation of range of motion (mROM, sROM) for each joint of lower limbs were calculated in one minute walking test. A motor performance index (E) defined as the sum of sROMs was proposed. We established two novel observer-independent measures of disability. Hip mROM was extremely sensitive in measuring lower limb motor impairment, being correlated with muscle strength and also altered in patients without clinically detectable disability. On the other hand, E index discriminated patients according to disability, being altered only in patients with moderate and severe disability, regardless of walking speed. It was strongly correlated with fatigue and patient-perceived health status. Inertial sensor-based gait analysis is feasible and can detect clinical and subclinical disability in multiple sclerosis.
Journal of NeuroEngineering and Rehabilitation, 2015
Background: Friedreich's ataxia (FRDA) is the most common hereditary autosomal recessive form of ... more Background: Friedreich's ataxia (FRDA) is the most common hereditary autosomal recessive form of ataxia. In this disease there is early manifestation of gait ataxia, and dysmetria of the arms and legs which causes impairment in daily activities that require fine manual dexterity. To date there is no cure for this disease. Some novel therapeutic approaches are ongoing in different steps of clinical trial. Development of sensitive outcome measures is crucial to prove therapeutic effectiveness. The aim of the study was to assess the reliability and sensitivity of quantitative and objective assessment of upper limb performance computed by means of the robotic device and to evaluate the correlation with clinical and functional markers of the disease severity.
Physiological Measurement, 2014
Magnetic inertial measurement unit systems (MIMU) offer the potential to perform joint kinematics... more Magnetic inertial measurement unit systems (MIMU) offer the potential to perform joint kinematics evaluation as an alternative to optoelectronic systems (OS). Several studies have reported the effect of indoor magnetic field disturbances on the MIMU's heading output, even though the overall effect on the evaluation of lower limb joint kinematics is not yet fully explored. The aim of the study is to assess the influence of indoor magnetic field distortion on gait analysis trials conducted with a commercial MIMU system. A healthy adult performed gait analysis sessions both indoors and outdoors. Data collected indoors were post-processed with and without a heading correction methodology performed with OS at the start of the gait trial. The performance of the MIMU system is characterized in terms of indices, based on the mean value of lower limb joint angles and the associated ROM, quantifying the system repeatability. We find that the effects of magnetic field distortion, such as the one we experienced in our lab, were limited to the transverse plane of each joint and to the frontal plane of the ankle. Sagittal plane values, instead, showed sufficient repeatability moving from outdoors to indoors. Our findings provide indications to clinicians on MIMU performance in the measurement of lower limb kinematics.
Sensors, 2014
In this work, we decided to apply a hierarchical weighted decision, proposed and used in other re... more 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 OPEN ACCESS Sensors 2014, 14 16213
Proceedings of 2nd International Electronic Conference on Sensors and Applications, 2015
Gait & Posture, 2009
Abstracts / Gait & Posture 30S (2009) S1-S153 models. We would, however, be tentative in using th... more Abstracts / Gait & Posture 30S (2009) S1-S153 models. We would, however, be tentative in using this system for faster movement speeds, at present.
Measurement, 2014
ABSTRACT This paper describes a novel functional body-to-sensor calibration procedure for inertia... more ABSTRACT This paper describes a novel functional body-to-sensor calibration procedure for inertial sensor-based gait analysis. The procedure is designed to be easily and autonomously performable by the subject, without the need for precise sensor positioning, or the performance of specific movements. The procedure consists in measuring the vertical axis during two static positions, and is not affected by magnetic field distortion. The procedure has been validated on ten healthy subjects using an optoelectronic system to measure the actual body-to-sensor rotation matrices. The effects of different sensor positions on each body segment, or different levels of subject inclination during the second static position of the procedure, resulted unnoticeable. The procedure showed accuracy and repeatability values less than 4° for each angle except for the ankle int–external rotation (9.7°, 7.2°). The results demonstrate the validity of the procedure, since they are comparable with those reported for the most-adopted protocols in gait analysis.
Gait & Posture, 2011
Abstracts / Gait & Posture 33S (2011) S1-S66 S13 the SMWT. Better performance was also noted in t... more Abstracts / Gait & Posture 33S (2011) S1-S66 S13 the SMWT. Better performance was also noted in the TUG and BBT scores in the RAGT group. Subjects also reported a reduced motor fatigue after training.
PLoS ONE, 2013
In this work, we develop a novel gait phase detection algorithm based on a hidden Markov model, w... more In this work, we develop a novel gait phase detection algorithm based on a hidden Markov model, which uses data from foot-mounted single-axis gyroscopes as input. We explore whether the proposed gait detection algorithm can generate equivalent results as a reference signal provided by force sensitive resistors (FSRs) for typically developing children (TD) and children with hemiplegia (HC). We find that the algorithm faithfully reproduces reference results in terms of high values of sensitivity and specificity with respect to FSR signals. In addition, the algorithm distinguishes between TD and HC and is able to assess the level of gait ability in patients. Finally, we show that the algorithm can be adapted to enable real-time processing with high accuracy. Due to the small, inexpensive nature of gyroscopes utilized in this study and the ease of implementation of the developed algorithm, this work finds application in the on-going development of active orthoses designed for therapy and locomotion in children with gait pathologies.
Sensors, 2015
Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for l... more Gait-phase recognition is a necessary functionality to drive robotic rehabilitation devices for lower limbs. Hidden Markov Models (HMMs) represent a viable solution, but they need subject-specific training, making data processing very time-consuming. Here, we validated an inter-subject procedure to avoid the intra-subject one in two, four and six gait-phase models in pediatric subjects. The inter-subject procedure consists in the identification of a standardized parameter set to adapt the model to measurements. We tested the inter-subject procedure both on scalar and distributed classifiers. Ten healthy children and ten hemiplegic children, each equipped with two Inertial Measurement Units placed on shank and foot, were recruited. The sagittal component of angular velocity was recorded by gyroscopes while subjects performed four walking trials on a treadmill. The goodness of classifiers was evaluated with the Receiver Operating Characteristic. The results provided a goodness from good to optimum for all examined classifiers (0 < G < 0.6), with the best performance for the distributed classifier in two-phase recognition (G = 0.02). Differences
Sensors (Basel, Switzerland), 2016
In the last years, gait phase partitioning has come to be a challenging research topic due to its... more 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 ex...
2015 IEEE International Conference on Rehabilitation Robotics (ICORR), 2015
2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings, 2015
In this paper we present and validate a methodology to avoid the training procedure of a classifi... more In this paper we present and validate a methodology to avoid the training procedure of a classifier based on an Hidden Markov Model (HMM) for a real-time gait recognition of two or four phases, implemented to control pediatric active orthoses of lower limb. The new methodology consists in the identification of a set of standardized parameters, obtained by a data set of angular velocities of healthy subjects age-matched. Sagittal angular velocities of lower limbs of ten typically developed children (TD) and ten children with hemiplegia (HC) were acquired by means of the tri-axial gyroscope embedded into Magnetic Inertial Measurement Units (MIMU). The actual sequence of gait phases was captured through a set of four foot switches. The experimental protocol consists in two walking tasks on a treadmill set at 1.0 and 1.5 km/h. We used the Goodness (G) as parameter, computed from Receiver Operating Characteristic (ROC) space, to compare the results obtained by the new methodology with the ones obtained by the subject-specific training of HMM via the Baum-Welch Algorithm. Paired-sample t-tests have shown no significant statistically differences between the two procedures when the gait phase detection was performed with the gyroscopes placed on the foot. Conversely, significant differences were found in data gathered by means of gyroscopes placed on shank. Actually, data relative to both groups presented G values in the range of good/optimum classifier (i.e. G ≤ 0.3), with better performance for the two-phase classifier model. In conclusion, the novel methodology here proposed guarantees the possibility to omit the off-line subject-specific training procedure for gait phase detection and it can be easily implemented in the control algorithm of active orthoses.