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Article ; Online: WARNING: A Wearable Inertial-Based Sensor Integrated with a Support Vector Machine Algorithm for the Identification of Faults during Race Walking.

Taborri, Juri / Palermo, Eduardo / Rossi, Stefano

2023 Volume 23, Issue 11

Abstract: Due to subjectivity in refereeing, the results of race walking are often questioned. To overcome this limitation, artificial-intelligence-based technologies have demonstrated their potential. The paper aims at presenting WARNING, an inertial-based ... ...

Abstract	Due to subjectivity in refereeing, the results of race walking are often questioned. To overcome this limitation, artificial-intelligence-based technologies have demonstrated their potential. The paper aims at presenting WARNING, an inertial-based wearable sensor integrated with a support vector machine algorithm to automatically identify race-walking faults. Two WARNING sensors were used to gather the 3D linear acceleration related to the shanks of ten expert race-walkers. Participants were asked to perform a race circuit following three race-walking conditions: legal, illegal with loss-of-contact and illegal with knee-bent. Thirteen machine learning algorithms, belonging to the decision tree, support vector machine and k-nearest neighbor categories, were evaluated. An inter-athlete training procedure was applied. Algorithm performance was evaluated in terms of overall accuracy, F1 score and G-index, as well as by computing the prediction speed. The quadratic support vector was confirmed to be the best-performing classifier, achieving an accuracy above 90% with a prediction speed of 29,000 observations/s when considering data from both shanks. A significant reduction of the performance was assessed when considering only one lower limb side. The outcomes allow us to affirm the potential of WARNING to be used as a referee assistant in race-walking competitions and during training sessions.
MeSH term(s)	Humans ; Support Vector Machine ; Walking ; Algorithms ; Artificial Intelligence ; Wearable Electronic Devices
Language	English
Publishing date	2023-05-31
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23115245
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Mixed Reality Environment and High-Dimensional Continuification Control for Swarm Robotics

Maffettone, Gian Carlo / Liguori, Lorenzo / Palermo, Eduardo / di Bernardo, Mario / Porfiri, Maurizio

2023

Abstract: A significant challenge in control theory and technology is to devise agile and less resource-intensive experiments for evaluating the performance and feasibility of control algorithms for the collective coordination of large-scale complex systems. Many ... ...

Abstract	A significant challenge in control theory and technology is to devise agile and less resource-intensive experiments for evaluating the performance and feasibility of control algorithms for the collective coordination of large-scale complex systems. Many new methodologies are based on macroscopic representations of the emerging system behavior, and can be easily validated only through numerical simulations, because of the inherent hurdle of developing full scale experimental platforms. In this paper, we introduce a novel hybrid mixed reality set-up for testing swarm robotics techniques, focusing on the collective motion of robotic swarms. This hybrid apparatus combines both real differential drive robots and virtual agents to create a heterogeneous swarm of tunable size. We validate the methodology by extending to higher dimensions, and investigating experimentally, continuification-based control methods for swarms. Our study demonstrates the versatility and effectiveness of the platform for conducting large-scale swarm robotics experiments. Also, it contributes new theoretical insights into control algorithms exploiting continuification approaches.
Keywords	Computer Science - Robotics ; Electrical Engineering and Systems Science - Systems and Control
Subject code	629
Publishing date	2023-10-02
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Automatic Detection of Faults in Race Walking: A Comparative Analysis of Machine-Learning Algorithms Fed with Inertial Sensor Data.

Taborri, Juri / Palermo, Eduardo / Rossi, Stefano

Sensors (Basel, Switzerland)

2019 Volume 19, Issue 6

Abstract: The validity of results in race walking is often questioned due to subjective decisions in the detection of faults. This study aims to compare machine-learning algorithms fed with data gathered from inertial sensors placed on lower-limb segments to ... ...

Abstract	The validity of results in race walking is often questioned due to subjective decisions in the detection of faults. This study aims to compare machine-learning algorithms fed with data gathered from inertial sensors placed on lower-limb segments to define the best-performing classifiers for the automatic detection of illegal steps. Eight race walkers were enrolled and linear accelerations and angular velocities related to pelvis, thighs, shanks, and feet were acquired by seven inertial sensors. The experimental protocol consisted of two repetitions of three laps of 250 m, one performed with regular race walking, one with loss-of-contact faults, and one with knee-bent faults. The performance of 108 classifiers was evaluated in terms of accuracy, recall, precision, F1-score, and goodness index. Generally, linear accelerations revealed themselves as more characteristic with respect to the angular velocities. Among classifiers, those based on the support vector machine (SVM) were the most accurate. In particular, the quadratic SVM fed with shank linear accelerations was the best-performing classifier, with an F1-score and a goodness index equal to 0.89 and 0.11, respectively. The results open the possibility of using a wearable device for automatic detection of faults in race walking competition.
Language	English
Publishing date	2019-03-25
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s19061461
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Using an ankle robotic device for motor performance and motor learning evaluation.

Martelli, Francesca / Palermo, Eduardo / Del Prete, Zaccaria / Rossi, Stefano

Heliyon

2020 Volume 6, Issue 1, Page(s) e03262

Abstract: In this paper we performed the evaluation of ankle motor performance and motor learning during a goal-directed task, executed using the pediAnklebot robot. The protocol consisted of 3 phases (Familiarization, Adaptation, and Wash Out) repeated one time ... ...

Abstract	In this paper we performed the evaluation of ankle motor performance and motor learning during a goal-directed task, executed using the pediAnklebot robot. The protocol consisted of 3 phases (Familiarization, Adaptation, and Wash Out) repeated one time for each movement direction (plantarflexion, dorsiflexion, inversion, and eversion). During Familiarization and Wash out subjects performed goal-directed movements in unperturbed environment, whereas during Adaptation phase, a curl viscous force field was applied and it was randomly removed 10 times out of 200. Ankle motor performance was evaluated by means of a set of indices grouped into: accuracy, smoothness, temporal, and stopping indices. Learning Index was calculated to study the motor learning during the adaptation phase, which was subdivided into 5 temporal intervals (target sets). The outcomes related to the ankle motor performance highlighted that the best performance in terms of accuracy and smoothness of the trajectories was obtained in dorsiflexion movements in the sagittal plane, and in inversion rotations in the frontal plane. Differences between movement directions revealed an anisotropic behavior of the ankle joint. Results of the Learning index showed a capability of the subjects to rapidly adapt to a perturbed force field depending on the magnitude of the perceived field.
Language	English
Publishing date	2020-01-24
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2020.e03262
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Measuring Biomechanical Risk in Lifting Load Tasks Through Wearable System and Machine-Learning Approach.

Conforti, Ilaria / Mileti, Ilaria / Del Prete, Zaccaria / Palermo, Eduardo

Sensors (Basel, Switzerland)

2020 Volume 20, Issue 6

Abstract: Ergonomics evaluation through measurements of biomechanical parameters in real time has a great potential in reducing non-fatal occupational injuries, such as work-related musculoskeletal disorders. Assuming a correct posture guarantees the avoidance of ... ...

Abstract	Ergonomics evaluation through measurements of biomechanical parameters in real time has a great potential in reducing non-fatal occupational injuries, such as work-related musculoskeletal disorders. Assuming a correct posture guarantees the avoidance of high stress on the back and on the lower extremities, while an incorrect posture increases spinal stress. Here, we propose a solution for the recognition of postural patterns through wearable sensors and machine-learning algorithms fed with kinematic data. Twenty-six healthy subjects equipped with eight wireless inertial measurement units (IMUs) performed manual material handling tasks, such as lifting and releasing small loads, with two postural patterns: correctly and incorrectly. Measurements of kinematic parameters, such as the range of motion of lower limb and lumbosacral joints, along with the displacement of the trunk with respect to the pelvis, were estimated from IMU measurements through a biomechanical model. Statistical differences were found for all kinematic parameters between the correct and the incorrect postures (
MeSH term(s)	Adult ; Algorithms ; Biomechanical Phenomena/physiology ; Ergonomics/methods ; Humans ; Lifting/adverse effects ; Lower Extremity/physiology ; Machine Learning ; Musculoskeletal Diseases/etiology ; Musculoskeletal Diseases/prevention & control ; Occupational Diseases/etiology ; Occupational Diseases/prevention & control ; Pattern Recognition, Automated/methods ; Posture/physiology ; Risk Assessment ; Wearable Electronic Devices ; Young Adult
Language	English
Publishing date	2020-03-11
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s20061557
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Estimation of Human Center of Mass Position through the Inertial Sensors-Based Methods in Postural Tasks: An Accuracy Evaluation.

Germanotta, Marco / Mileti, Ilaria / Conforti, Ilaria / Del Prete, Zaccaria / Aprile, Irene / Palermo, Eduardo

Sensors (Basel, Switzerland)

2021 Volume 21, Issue 2

Abstract: The estimation of the body's center of mass (CoM) trajectory is typically obtained using force platforms, or optoelectronic systems (OS), bounding the assessment inside a laboratory setting. The use of magneto-inertial measurement units (MIMUs) allows ... ...

Abstract	The estimation of the body's center of mass (CoM) trajectory is typically obtained using force platforms, or optoelectronic systems (OS), bounding the assessment inside a laboratory setting. The use of magneto-inertial measurement units (MIMUs) allows for more ecological evaluations, and previous studies proposed methods based on either a single sensor or a sensors' network. In this study, we compared the accuracy of two methods based on MIMUs. Body CoM was estimated during six postural tasks performed by 15 healthy subjects, using data collected by a single sensor on the pelvis (Strapdown Integration Method, SDI), and seven sensors on the pelvis and lower limbs (Biomechanical Model, BM). The accuracy of the two methods was compared in terms of RMSE and estimation of posturographic parameters, using an OS as reference. The RMSE of the SDI was lower in tasks with little or no oscillations, while the BM outperformed in tasks with greater CoM displacement. Moreover, higher correlation coefficients were obtained between the posturographic parameters obtained with the BM and the OS. Our findings showed that the estimation of CoM displacement based on MIMU was reasonably accurate, and the use of the inertial sensors network methods should be preferred to estimate the kinematic parameters.
MeSH term(s)	Biomechanical Phenomena ; Humans ; Lower Extremity ; Pelvis
Language	English
Publishing date	2021-01-16
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s21020601
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: A novel protocol to evaluate ankle movements during reaching tasks using pediAnklebot.

Martelli, Francesca / Palermo, Eduardo / Rossi, Stefano

IEEE ... International Conference on Rehabilitation Robotics : [proceedings

2017 Volume 2017, Page(s) 326–331

Abstract: The aim of the study is to design a novel protocol to characterize the ankle movements during dorsal and plantar flexion reaching tasks using the pediAnklebot. Five healthy children were instructed to control a pointer and hit targets appearing on the ... ...

Abstract	The aim of the study is to design a novel protocol to characterize the ankle movements during dorsal and plantar flexion reaching tasks using the pediAnklebot. Five healthy children were instructed to control a pointer and hit targets appearing on the monitor, by moving their ankle alternatively up and down. The protocol consisted of 60 targets, 30 up and 30 down, reachable via dorsiflexion and plantarflexion movements, respectively. Ankle angular displacements and torques were gathered by encoders and load cells embedded in the robot. Ankle motor performance was evaluated by means of kinematic, submovements and dynamic indices. Results suggest that (i) plantarflexion movements are faster and more accurate than the dorsiflexion ones, but children are able to perform with a higher level of smoothness the latter ones; (ii) children are able to stop the ankle movement more easily at the end of dorsiflexion rather than plantarflexion; (iii) the central nervous system plans plantarflexion and dorsiflexion movements with the same efficiency; (iv) children apply different torque levels during the two motor tasks and they cannot balance the inversion and eversion moments during dorsiflexion. These findings provide an important starting point for the assessment of a reference baseline of motor indices for the ankle joint.
Language	English
Publishing date	2017-07
Publishing country	United States
Document type	Journal Article
ISSN	1945-7901
ISSN (online)	1945-7901
DOI	10.1109/ICORR.2017.8009268
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Article: On the Reliability and Repeatability of Surface Electromyography Factorization by Muscle Synergies in Daily Life Activities.

Taborri, Juri / Palermo, Eduardo / Del Prete, Zaccaria / Rossi, Stefano

Applied bionics and biomechanics

2018 Volume 2018, Page(s) 5852307

Abstract: Muscle synergy theory is a new appealing approach for different research fields. This study is aimed at evaluating the robustness of EMG reconstruction via muscle synergies and the repeatability of muscle synergy parameters as potential ... ...

Abstract	Muscle synergy theory is a new appealing approach for different research fields. This study is aimed at evaluating the robustness of EMG reconstruction via muscle synergies and the repeatability of muscle synergy parameters as potential neurophysiological indices. Eight healthy subjects performed walking, stepping, running, and ascending and descending stairs' trials for five repetitions in three sessions. Twelve muscles of the dominant leg were analyzed. The "nonnegative matrix factorization" and "variability account for" were used to extract muscle synergies and to assess EMG goodness reconstruction, respectively. Intraclass correlation was used to quantify methodology reliability. Cosine similarity and coefficient of determination assessed the repeatability of the muscle synergy vectors and the temporal activity patterns, respectively. A 4-synergy model was selected for EMG signal factorization. Intraclass correlation was excellent for the overall reconstruction, while it ranged from fair to excellent for single muscles. The EMG reconstruction was found repeatable across sessions and subjects. Considering the selection of neurophysiological indices, the number of synergies was not repeatable neither within nor between subjects. Conversely, the cosine similarity and coefficient of determination values allow considering the muscle synergy vectors and the temporal activity patterns as potential neurophysiological indices due to their similarity both within and between subjects. More specifically, some synergies in the 4-synergy model reveal themselves as more repeatable than others, suggesting focusing on them when seeking at the neurophysiological index identification.
Language	English
Publishing date	2018-11-22
Publishing country	Egypt
Document type	Journal Article
ZDB-ID	2179924-6
ISSN	1754-2103 ; 1176-2322
ISSN (online)	1754-2103
ISSN	1176-2322
DOI	10.1155/2018/5852307
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Article ; Online: Early balance impairment in Parkinson's Disease: Evidence from Robot-assisted axial rotations.

Zampogna, Alessandro / Mileti, Ilaria / Martelli, Francesca / Paoloni, Marco / Del Prete, Zaccaria / Palermo, Eduardo / Suppa, Antonio

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology

2021 Volume 132, Issue 10, Page(s) 2422–2430

Abstract: Objective: Early postural instability (PI) is a red flag for the diagnosis of Parkinson's disease (PD). Several patients, however, fall within the first three years of disease, particularly when turning. We investigated whether PD patients, without ... ...

Abstract	Objective: Early postural instability (PI) is a red flag for the diagnosis of Parkinson's disease (PD). Several patients, however, fall within the first three years of disease, particularly when turning. We investigated whether PD patients, without clinically overt PI, manifest abnormal reactive postural responses to ecological perturbations resembling turning. Methods: Fifteen healthy subjects and 20 patients without clinically overt PI, under and not under L-Dopa, underwent dynamic posturography during axial rotations around the longitudinal axis, provided by a robotic mechatronic platform. We measured reactive postural responses, including body displacement and reciprocal movements of the head, trunk, and pelvis, by using a network of three wearable inertial sensors. Results: Patients showed higher body displacement of the head, trunk and pelvis, and lower joint movements at the lumbo-sacral junction than controls. Conversely, movements at the cranio-cervical junction were normal in PD. L-Dopa left reactive postural responses unchanged. Conclusions: Patients with PD without clinically overt PI manifest abnormal reactive postural responses to axial rotations, unresponsive to L-Dopa. The biomechanical model resulting from our experimental approach supports novel pathophysiological hypotheses of abnormal axial rotations in PD. Significance: PD patients without clinically overt PI present subclinical balance impairment during axial rotations, unresponsive to L-Dopa.
MeSH term(s)	Aged ; Antiparkinson Agents/pharmacology ; Antiparkinson Agents/therapeutic use ; Early Diagnosis ; Female ; Humans ; Levodopa/pharmacology ; Levodopa/therapeutic use ; Male ; Middle Aged ; Parkinson Disease/diagnosis ; Parkinson Disease/drug therapy ; Parkinson Disease/physiopathology ; Postural Balance/drug effects ; Postural Balance/physiology ; Robotics/instrumentation ; Robotics/methods ; Rotation ; Wearable Electronic Devices
Chemical Substances	Antiparkinson Agents ; Levodopa (46627O600J)
Language	English
Publishing date	2021-07-28
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	1463630-x
ISSN	1872-8952 ; 0921-884X ; 1388-2457
ISSN (online)	1872-8952
ISSN	0921-884X ; 1388-2457
DOI	10.1016/j.clinph.2021.06.023
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Article ; Online: Gait Partitioning Methods: A Systematic Review.

Taborri, Juri / Palermo, Eduardo / Rossi, Stefano / Cappa, Paolo

Sensors (Basel, Switzerland)

2016 Volume 16, Issue 1

Abstract: 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 ... ...

Abstract	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.
MeSH term(s)	Accelerometry ; Clothing ; Electromyography ; Gait/physiology ; Humans ; Monitoring, Ambulatory ; Signal Processing, Computer-Assisted
Language	English
Publishing date	2016-01-06
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review ; Systematic Review
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s16010066
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