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See detail3D analysis of gait using accelerometer measurements
Boutaayamou, Mohamed ULg; Schwartz, Cédric ULg; Stamatakis, Julien et al

Scientific conference (2013, November 07)

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See detailValidation of an accelerometer-based approach to quantify gait events
Boutaayamou, Mohamed ULg; Schwartz, Cédric ULg; Stamatakis, Julien et al

Poster (2013, June)

Researchers rarely provide solid performance and validation information about their acceleometer-based approaches to human gait analysis. We present here a novel signal processing and analysis algorithm ... [more ▼]

Researchers rarely provide solid performance and validation information about their acceleometer-based approaches to human gait analysis. We present here a novel signal processing and analysis algorithm that automatically extracts four consecutive fundamental events of walking: heel strike (HS), toe strike (TS), heel off (HO), and toe off (TO). In addition, we validate this accelerometer-based technique by comparing these extracted gait events with those obtained by a kinematic 3D analysis system and a force plate, used as gold standards. [less ▲]

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See detailValidated Extraction of Gait Events from 3D Accelerometer Recordings
Boutaayamou, Mohamed ULg; Schwartz, Cédric ULg; Stamatakis, Julien et al

in IEEE International Conference on 3D Imaging (IC3D) (2012, December)

This work is part of a project that deals with the three-dimensional (3D) analysis of normal and pathological gaits based on a newly developed system for clinical applications, using low-cost wireless ... [more ▼]

This work is part of a project that deals with the three-dimensional (3D) analysis of normal and pathological gaits based on a newly developed system for clinical applications, using low-cost wireless accelerometers and a signal processing algorithm. This system automatically extracts relevant gait events such as the heel strikes (HS) and the toe-offs (TO), which characterize the stance and the swing phases of walking. The performances of the low-cost accelerometer hardware and related algorithm have been compared to those obtained by a kinematic 3D analysis system and a force plate, used as gold standard methods. The HS and TO times obtained from the gait data of 7 healthy volunteers (147 trials) have been found to be (mean ± standard deviation) 0.42±7.92 ms and 3.11±10.08 ms later than those determined by the force plate, respectively. The experimental results demonstrate that the new hardware and associated algorithm constitute an effective low-cost gait analysis system, which could thus be used for the assessment of mobility in routine clinical practice. [less ▲]

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See detailEffect of finger tapping frequency on abnormal subthalamic nucleus oscillations in Parkinson’s disease
Stamatakis, Julien; Noirhomme, Quentin ULg; Orban, Jonhatan et al

Poster (2012, October)

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See detailResting-state EEG study of comatose patients: a connectivity and frequency analysis to find differences between vegetative and minimally conscious states.
Lehembre, Remy ULg; Bruno, Marie-Aurélie ULg; Vanhaudenhuyse, Audrey ULg et al

in Functional Neurology (2012), 27(1), 41-47

The aim of this study was to look for differences in the power spectra and in EEG connectivity measures between patients in the vegetative state (VS/UWS) and patients in the minimally conscious state (MCS ... [more ▼]

The aim of this study was to look for differences in the power spectra and in EEG connectivity measures between patients in the vegetative state (VS/UWS) and patients in the minimally conscious state (MCS). The EEG of 31 patients was recorded and analyzed. Power spectra were obtained using modern multitaper methods. Three connectivity measures (coherence, the imaginary part of coherency and the phase lag index) were computed. Of the 31 patients, 21 were diagnosed as MCS and 10 as VS/UWS using the Coma Recovery Scale-Revised (CRS-R). EEG power spectra revealed differences between the two conditions. The VS/UWS patients showed increased delta power but decreased alpha power compared with the MCS patients. Connectivity measures were correlated with the CRS-R diagnosis; patients in the VS/UWS had significantly lower connectivity than MCS patients in the theta and alpha bands. Standard EEG recorded in clinical conditions could be used as a tool to help the clinician in the diagnosis of disorders of consciousness. [less ▲]

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See detailGait feature extraction in Parkinson's disease using low-cost accelerometers
Stamatakis, Julien; Cremers, Julien ULg; Maquet, Didier ULg et al

Poster (2011)

The clinical hallmarks of Parkinson’s disease (PD) are movement poverty and slowness (i.e. bradykinesia), muscle rigidity, limb tremor or gait disturbances. Parkinson’s gait include slowness, shuffling ... [more ▼]

The clinical hallmarks of Parkinson’s disease (PD) are movement poverty and slowness (i.e. bradykinesia), muscle rigidity, limb tremor or gait disturbances. Parkinson’s gait include slowness, shuffling, short steps, freezing of gait (FoG) and/or asymmetries in gait. There are currently no validated clinical instruments or device that allow a full characterization of gait disturbances in PD. As a step towards this goal, a four accelerometer-based system is proposed to increase the number of parameters that can be extracted to characterize parkinsonian gait disturbances such as FoG or gait asymmetries. After developing the hardware, an algorithm has been developed, that automatically epoched the signals on a stride-by-stride basis and quantified, among others, the gait velocity, the stride time,the stance and swing phases, the single and double support phases or the maximum acceleration at toe-off, as validated by visual inspection of video recordings during the task. The results obtained in a PD patient and an healthy volunteer are presented. The FoG detection will be improved using time-frequency analysis and the system is about to be validated with a state-of-the-art 3D movement analysis system. [less ▲]

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See detailFinger Tapping feature extraction in Parkinson's disease using low-cost accelerometers
Stamatakis, Julien; Cremers, Julien ULg; Macq, Benoït et al

in Proceedings 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2010) (2010)

The clinical hallmarks of Parkinson's disease (PD) are movement poverty and slowness (i.e. bradykinesia), muscle rigidity and limb tremor. The physicians usually quantify these motor disturbances by ... [more ▼]

The clinical hallmarks of Parkinson's disease (PD) are movement poverty and slowness (i.e. bradykinesia), muscle rigidity and limb tremor. The physicians usually quantify these motor disturbances by assigning a severity score according to validated but time-consuming clinical scales such as the Unified Parkinson's Disease Rating Scale (UPDRS) - part III. These clinical ratings are however prone to subjectivity and inter-rater variability. The PD medical community is therefore looking for a faster and more objective rating method. As a first step towards this goal, a tri-axial accelerometer-based system is proposed as patients are engaged in a repetitive finger tapping task, which is classically used to assess bradykinesia in the UPDRS-III. After developing the hardware, an algorithm has been developed, that automatically epoched the signal on a trial-by-trial basis and quantified, among others, movement speed, amplitude, hesitations or halts as validated by visual inspection of video recordings during the task. The results obtained in a PD patient and an healthy volunteer are presented. Preliminary results show that PD patients and healthy volunteers have different features profiles, so that a classifier could be set up to predict objective UPDRS-III scores. [less ▲]

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See detailNon-Rigid Object Tracker Based On a Robust Combination of Parametric Active Contour and Point Distribution Model
Olszewska, Joanna; Mathes, Tom; De Vleeschouwer, Christophe et al

in Proceedings of the SPIE Conference on Visual Communication and Image Processing (2007)

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See detailTRICTRAC Video Dataset: Public HDTV Synthetic Soccer Video Sequences With Ground Truth
Desurmont, Xavier; Hayet, Jean*-Bernard; Delaigle, Jean*-Fran et al

in Workshop on Computer Vision Based Analysis in Sport Environments (CVBASE) (2006)

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See detailA Modular Multi-camera Framework for Team Sport Tracking
Hayet, Jean-Bernard; Mathes, Thomas; Czyz, Jacek et al

Conference (2005)

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See detailRegistration and real-time visualization of transcranial magnetic stimulation with 3-D MR images.
Noirhomme, Quentin ULg; Ferrant, Matthieu; Vandermeeren, Yves et al

in IEEE Transactions on Biomedical Engineering (2004), 51(11), 1994-2005

This paper describes a method for registering and visualizing in real-time the results of transcranial magnetic stimulations (TMS) in physical space on the corresponding anatomical locations in MR images ... [more ▼]

This paper describes a method for registering and visualizing in real-time the results of transcranial magnetic stimulations (TMS) in physical space on the corresponding anatomical locations in MR images of the brain. The method proceeds in three main steps. First, the patient scalp is digitized in physical space with a magnetic-field digitizer, following a specific digitization pattern. Second, a registration process minimizes the mean square distance between those points and a segmented scalp surface extracted from the magnetic resonance image. Following this registration, the physician can follow the change in coil position in real-time through the visualization interface and adjust the coil position to the desired anatomical location. Third, amplitude of motor evoked potentials can be projected onto the segmented brain in order to create functional brain maps. The registration has subpixel accuracy in a study with simulated data, while we obtain a point to surface root-mean-square error of 1.17+/-0.38 mm in a 24 subject study. [less ▲]

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See detailMorphological image sketch coding
Simon, Benoît; Macq, Benoît; Van Droogenbroeck, Marc ULg

in Workshop on Circuits, Systems and Signal Processing, Proceedings (1993, March)

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