References of "Verly, Jacques"
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See detailValidated assessment of gait sub-phase durations in older adults using an accelerometer-based ambulatory system
Boutaayamou, Mohamed ULiege; GILLAIN, Sophie ULiege; Schwartz, Cédric ULiege et al

in Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) (in press)

Validated extraction of gait sub-phase durations using an ambulatory accelerometer-based system is a current unmet need to quantify subtle changes during the walking of older adults. In this paper, we ... [more ▼]

Validated extraction of gait sub-phase durations using an ambulatory accelerometer-based system is a current unmet need to quantify subtle changes during the walking of older adults. In this paper, we describe (1) a signal processing algorithm to automatically extract not only durations of stride, stance, swing, and double support phases, but also durations of sub-phases that refine the stance and swing phases from foot-worn accelerometer signals in comfortable walking of older adults, and (2) the validation of this extraction using reference data provided by a gold standard system. The results show that we achieve a high agreement between our method and the reference method in the extraction of (1) the temporal gait events involved in the estimation of the phase/sub-phase durations, namely heel strike (HS), toe strike (TS), toe-off (TO), maximum of heel clearance (MHC), and maximum of toe clearance (MTC), with an accuracy and precision that range from ‒3.6 ms to 4.0 ms, and 6.5 ms to 12.0 ms, respectively, and (2) the gait phase/sub-phase durations, namely stride, stance, swing, double support phases, and HS to TS, TO to MHC, MHC to MTC, and MTC to HS sub-phases, with an accuracy and precision that range from ‒4 ms to 5 ms, and 9 ms to 15 ms, respectively, in comfortable walking of a thirty-eight older adults ( (mean ± standard deviation) 71.0 ± 4.1 years old). This demonstrates that the developed accelerometer-based algorithm can extract validated temporal gait events and phase/sub-phase durations, in comfortable walking of older adults, with a promising degree of accuracy/precision compared to reference data, warranting further studies. [less ▲]

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Peer Reviewed
See detailExcellent Potential of Geometric Brownian Motion (GBM) as a Random Process Model for Level of Drowsiness Signals
Ebrahimbabaie Varnosfaderani, Pouyan ULiege; Verly, Jacques ULiege

Conference (2018, January 20)

We show that Geometric Brownian Motion (GBM) appears to be an excellent choice of random process model to describe mathematically the real-life signals that represent the evolution with time of the level ... [more ▼]

We show that Geometric Brownian Motion (GBM) appears to be an excellent choice of random process model to describe mathematically the real-life signals that represent the evolution with time of the level of drowsiness (LoD) of an individual, such as a driver. We collected data from thirty (30) healthy participants, who each underwent three tests (either driving in a simulator or performing Psychomotor Vigilance Tests) at successive levels of sleep deprivation. During each test, the LoD was produced by a photooculography (POG) based device designed and built by our team. We so obtained a total of 90 LoD signals. For each, we applied statistical methods to determine whether a GBM was a valid model for it. All 90 signals passed statistical tests of normality and independency, meaning that each can be modeled by GBM, thereby showing the excellent potential of GBM as a random process model for LoD signals. This finding could lead to the development of a number of innovative means for predicting the evolution of the LoD and the occurrence of related events beyond the present moment. The resulting technology should help reduce the number of accidents due to drowsy driving. [less ▲]

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See detailSome novel applications of virtual reality (VR) in the domain of health
Grogna, David ULiege; Stassart, Céline ULiege; Bragard, Isabelle ULiege et al

Conference (2017, December 12)

Detailed reference viewed: 20 (4 ULiège)
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See detailA gait cycle partitioning method using a foot-worn accelerometer system
Boutaayamou, Mohamed ULiege; Bruls, Olivier ULiege; Denoël, Vincent ULiege et al

Conference (2017, November 30)

Detailed reference viewed: 75 (3 ULiège)
Peer Reviewed
See detailA gait cycle partitioning method using a foot-worn accelerometer system
Boutaayamou, Mohamed ULiege; Bruls, Olivier ULiege; Denoël, Vincent ULiege et al

Conference (2017, November 30)

Detailed reference viewed: 14 (0 ULiège)
Peer Reviewed
See detailRelationship between brain activity and ocular movements during wakefulness and drowsiness
François, Clémentine ULiege; Wertz, Jérôme; Verly, Jacques ULiege

Poster (2017, October 11)

Detailed reference viewed: 25 (8 ULiège)
Peer Reviewed
See detailA Novel Accelerometer-Based Method for Stride Length Estimation
Boutaayamou, Mohamed ULiege; Schwartz, Cédric ULiege; Denoël, Vincent ULiege et al

Poster (2017, July 14)

We demonstrate the feasibility of accurately and precisely estimating the left/right average stride length from measured heel/toe accelerations in the gait of healthy, old adults. Our approach relies on ... [more ▼]

We demonstrate the feasibility of accurately and precisely estimating the left/right average stride length from measured heel/toe accelerations in the gait of healthy, old adults. Our approach relies on (1) a novel method that uses only accelerometer data without the need of additional data from, e.g., gyroscopes and/or magnetometers, and on (2) the validation of the results using reference 3D optoelectronic system data. [less ▲]

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See detailCubesats activities at the University of Liège
Werner, Xavier ULiege; Broun, Valery ULiege; De Dijcker, Sébastien ULiege et al

Conference given outside the academic context (2017)

Detailed reference viewed: 22 (4 ULiège)
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See detailOUFTI-2 educational CubeSat project of University of Liège, Belgium
Guillaume, Thibaut; Rikir, Adrien; De Dijcker, Sébastien ULiege et al

Scientific conference (2017, May 03)

Detailed reference viewed: 179 (73 ULiège)
See detailAmbulatory System for Gait Analysis
Boutaayamou, Mohamed ULiege; Bruls, Olivier ULiege; Croisier, Jean-Louis ULiege et al

Conference (2017, April 29)

We describe the principle and use of a wireless, 3-axis accelerometer-based ambulatory system that records acceleration signals and automatically analyses them to characterize normal and pathological gait ... [more ▼]

We describe the principle and use of a wireless, 3-axis accelerometer-based ambulatory system that records acceleration signals and automatically analyses them to characterize normal and pathological gait. The associated algorithm is versatile enough to detect, on a stride-by-stride basis, refined gait parameters that quantify subtle gait disturbances in, e.g., in Parkinson’s disease in a rater-independent way. The experimental results show the potential of the developed accelerometer-based technique to be used in neurology (e.g., characterization of Parkinsonian gait: slowness, shuffling, short steps, freezing of gait, asymmetries in gait), rehabilitation, geriatrics (ex. monitoring activity parameters in the elderly), orthopedics and sport. [less ▲]

Detailed reference viewed: 35 (6 ULiège)