A virtual ball task driven by forearm movements for neuro-rehabilitation

Petracca, Andrea; Carrieri, Marika; Avola, Danilo; Moro, Sara Basso; Brigadoi, Sabrina; Lancia, Stefania; Spezialetti, Matteo; Ferrari, Marco; Quaresrma, V; Placuir, G

doi:10.1109/icvr.2015.7358600

Cited by 23 publications

(9 citation statements)

References 10 publications

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“…On the one hand, several works focused on hand motor recovery using only the LMC and a virtual environment are found. In [ 20 ], the prefrontal cortex haemodynamic responses during the executions of demanding manual tasks performed in a semi-immersive VR environment are studied. The LMC is used to track the hand movements and to enable subjects to transpose their hand movements within a virtual 3D task.…”

Section: Related Workmentioning

confidence: 99%

Effectiveness of Serious Games for Leap Motion on the Functionality of the Upper Limb in Parkinson’s Disease: A Feasibility Study

Oña

Balaguer

Cano‐de‐la‐Cuerda

et al. 2018

Computational Intelligence and Neuroscience

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The design and application of Serious Games (SG) based on the Leap Motion sensor are presented as a tool to support the rehabilitation therapies for upper limbs. Initially, the design principles and their implementation are described, focusing on improving both unilateral and bilateral manual dexterity and coordination. The design of the games has been supervised by specialized therapists. To assess the therapeutic effectiveness of the proposed system, a protocol of trials with Parkinson's patients has been defined. Evaluations of the physical condition of the participants in the study, at the beginning and at the end of the treatment, are carried out using standard tests. The specific measurements of each game give the therapist more detailed information about the patients' evolution after finishing the planned protocol. The obtained results support the fact that the set of developed video games can be combined to define different therapy protocols and that the information obtained is richer than the one obtained through current clinical metrics, serving as method of motor function assessment.

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Section: Related Workmentioning

confidence: 99%

Effectiveness of Serious Games for Leap Motion on the Functionality of the Upper Limb in Parkinson’s Disease: A Feasibility Study

Oña

Balaguer

Cano‐de‐la‐Cuerda

et al. 2018

Computational Intelligence and Neuroscience

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“…In the last decades, vision-based systems are becoming increasingly important in supporting a wide range of application areas, including environment modelling for moving cameras [1][2][3][4][5], human action and event recognition [6][7][8][9], target and object detection [10][11][12][13][14][15][16]; even in areas such as medical image analysis [17][18][19][20][21][22][23], emotion or deception recognition [24][25][26][27][28][29], and immersive rehabilitation by serious games [30][31][32][33][34][35], these systems are, now, of daily use. At the same time, the last 10 years have seen substantial improvements of small-scale Unmanned Aerial Vehicles (UAVs), hereinafter UAVs, in terms of flight time, automatic control, embedded processing, and remote transmission.…”

Section: Introductionmentioning

confidence: 99%

Low-Altitude Aerial Video Surveillance via One-Class SVM Anomaly Detection from Textural Features in UAV Images

et al. 2021

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In recent years, small-scale Unmanned Aerial Vehicles (UAVs) have been used in many video surveillance applications, such as vehicle tracking, border control, dangerous object detection, and many others. Anomaly detection can represent a prerequisite of many of these applications thanks to its ability to identify areas and/or objects of interest without knowing them a priori. In this paper, a One-Class Support Vector Machine (OC-SVM) anomaly detector based on customized Haralick textural features for aerial video surveillance at low-altitude is presented. The use of a One-Class SVM, which is notoriously a lightweight and fast classifier, enables the implementation of real-time systems even when these are embedded in low-computational small-scale UAVs. At the same time, the use of textural features allows a vision-based system to detect micro and macro structures of an analyzed surface, thus allowing the identification of small and large anomalies, respectively. The latter aspect plays a key role in aerial video surveillance at low-altitude, i.e., 6 to 15 m, where the detection of common items, e.g., cars, is as important as the detection of little and undefined objects, e.g., Improvised Explosive Devices (IEDs). Experiments obtained on the UAV Mosaicking and Change Detection (UMCD) dataset show the effectiveness of the proposed system in terms of accuracy, precision, recall, and F1-score, where the model achieves a 100% precision, i.e., never misses an anomaly, but at the expense of a reasonable trade-off in its recall, which still manages to reach up to a 71.23% score. Moreover, when compared to classical Haralick textural features, the model obtains significantly higher performances, i.e., ≈20% on all metrics, further demonstrating the approach effectiveness.

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“…Tracking-based gloves consist of computer vision algorithms for the analysis and interpretation of videos from depth sensing sensors to calculate hand kinematics in real time [ 10 , 15 , 16 , 17 , 18 , 19 ]. Besides depth sensors, LEAP [ 20 ] is a small and low-cost hand 3D tracking device characterized by high-resolution and high-reactivity [ 21 , 22 , 23 ], used in VR [ 24 ], and has been recently presented and tested with success in the hand rehabilitation, with exercises designed in VR environments [ 25 ]. Despite the advantages of using LEAP with VR, a single sensor does not allow accurate quantitative evaluation of hand and fingers tracking in case of occlusions.…”

Section: Introductionmentioning

confidence: 99%

Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation

Placidi

Cinque

Polsinelli

et al. 2018

Sensors

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Hand rehabilitation is fundamental after stroke or surgery. Traditional rehabilitation requires a therapist and implies high costs, stress for the patient, and subjective evaluation of the therapy effectiveness. Alternative approaches, based on mechanical and tracking-based gloves, can be really effective when used in virtual reality (VR) environments. Mechanical devices are often expensive, cumbersome, patient specific and hand specific, while tracking-based devices are not affected by these limitations but, especially if based on a single tracking sensor, could suffer from occlusions. In this paper, the implementation of a multi-sensors approach, the Virtual Glove (VG), based on the simultaneous use of two orthogonal LEAP motion controllers, is described. The VG is calibrated and static positioning measurements are compared with those collected with an accurate spatial positioning system. The positioning error is lower than 6 mm in a cylindrical region of interest of radius 10 cm and height 21 cm. Real-time hand tracking measurements are also performed, analysed and reported. Hand tracking measurements show that VG operated in real-time (60 fps), reduced occlusions, and managed two LEAP sensors correctly, without any temporal and spatial discontinuity when skipping from one sensor to the other. A video demonstrating the good performance of VG is also collected and presented in the Supplementary Materials. Results are promising but further work must be done to allow the calculation of the forces exerted by each finger when constrained by mechanical tools (e.g., peg-boards) and for reducing occlusions when grasping these tools. Although the VG is proposed for rehabilitation purposes, it could also be used for tele-operation of tools and robots, and for other VR applications.

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A virtual ball task driven by forearm movements for neuro-rehabilitation

Cited by 23 publications

References 10 publications

Effectiveness of Serious Games for Leap Motion on the Functionality of the Upper Limb in Parkinson’s Disease: A Feasibility Study

Effectiveness of Serious Games for Leap Motion on the Functionality of the Upper Limb in Parkinson’s Disease: A Feasibility Study

Low-Altitude Aerial Video Surveillance via One-Class SVM Anomaly Detection from Textural Features in UAV Images

Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation

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