References of "Boutaayamou, Mohamed"
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See detailGait pattern of healthy old people for fast walking condition
GILLAIN, Sophie ULg; Boutaayamou, Mohamed ULg; Schwartz, Cédric ULg et al

in Gerontechnology (2016, September)

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See detailGait pattern of healthy old people for dual task walking condition
GILLAIN, Sophie ULg; Boutaayamou, Mohamed ULg; Schwartz, Cédric ULg et al

in Gerontechnology (2016, September)

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See detailExtraction of temporal gait parameters using a reduced number of wearable accelerometers
Boutaayamou, Mohamed ULg; Denoël, Vincent ULg; Bruls, Olivier ULg et al

in Proceedings of the 9th International Conference on Bio-inspired Systems and Signal Processing (2016)

Wearable inertial systems often require many sensing units in order to reach an accurate extraction of temporal gait parameters. Reconciling easy and fast handling in daily clinical use and accurate ... [more ▼]

Wearable inertial systems often require many sensing units in order to reach an accurate extraction of temporal gait parameters. Reconciling easy and fast handling in daily clinical use and accurate extraction of a substantial number of relevant gait parameters is a challenge. This paper describes the implementation of a new accelerometer-based method that accurately and precisely detects gait events/parameters from acceleration signals measured from only two accelerometers attached on the heels of the subject’s usual shoes. The first step of the proposed method uses a gait segmentation based on the continuous wavelet transform (CWT) that provides only a rough estimation of motionless periods defining relevant local acceleration signals. The second step uses the CWT and a novel piecewise-linear fitting technique to accurately extract, from these local acceleration signals, gait events, each labelled as heel strike (HS), toe strike (TS), heel-off (HO), toe-off (TO), or heel clearance (HC). A stride-by-stride validation of these extracted gait events was carried out by comparing the results with reference data provided by a kinematic 3D analysis system (used as gold standard) and a video camera. The temporal accuracy ± precision of the gait events were for HS: 7.2 ms ± 22.1 ms, TS: 0.7 ms ± 19.0 ms, HO: ‒3.4 ms ± 27.4 ms, TO: 2.2 ms ± 15.7 ms, and HC: 3.2 ms ± 17.9 ms. In addition, the occurrence times of right/left stance, swing, and stride phases were estimated with a mean error of ‒6 ms ± 15 ms, ‒5 ms ± 17 ms, and ‒6 ms ± 17 ms, respectively. The accuracy and precision achieved by the extraction algorithm for healthy subjects, the simplification of the hardware (through the reduction of the number of accelerometer units required), and the validation results obtained, convince us that the proposed accelerometer-based system could be extended for assessing pathological gait (e.g., for patients with Parkinson’s disease). [less ▲]

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See detailGait quantification through accelerometers and clinical tests: application to pathological gait
DEMONCEAU, Marie ULg; Boutaayamou, Mohamed ULg; Maquet, Didier ULg et al

Conference (2015, January 30)

Gait gives essential information to physiotherapists in the screening and follow-up of their patients suffering from orthopaedic, geriatric or neurologic diseases. Most of time, clinical practitioners ... [more ▼]

Gait gives essential information to physiotherapists in the screening and follow-up of their patients suffering from orthopaedic, geriatric or neurologic diseases. Most of time, clinical practitioners rely on visual observation of their patients during specific clinical tests that can highlight gait abnormalities (e,g., the Tinetti assessment tool, the timed up and go test, the 6 minutes walking test), but these tests provide little quantified information about gait. These rough methods are also limited by inter-rater subjectivity and lack of acuteness in the detection of subtle impairments. On the other hand, instrumented gait analyses offer a sharper investigation with the ability to record and quantify gait events that cannot be caught at simple visual observation. Unfortunately, cutting edge technologies often pay the price of a limited number of strides extracted, the need of a strictly controlled laboratory environment, development and maintenance by a specialized staff. For these reasons, instrumented gait analysis may stand beyond the financial and technical reach of many rehabilitative centres and private practitioners. Accelerometer technologies have considerably developed with the progress of wireless technologies. These lightweight and low-cost sensors allow quantified gait analyses that are not restricted to a laboratory environment but can also be used in medical offices and in combination with common clinical gait tests. This presentation relates the experiences of our departments with accelerometer systems and clinical testing in gait analysis of patients suffering from Parkinson’s disease. The aim of this intervention is to cross ideas and knowledge of clinical practitioners and engineers in the development a new gait analysis tool that could integrate routine evaluation of patients suffering from Parkinson’s disease and other conditions characterized by gait impairments. [less ▲]

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See detailDevelopment and validation of an accelerometer-based method for quantifying gait events
Boutaayamou, Mohamed ULg; Schwartz, Cédric ULg; Stamatakis, Julien et al

in Medical Engineering & Physics (2015)

An original signal processing algorithm is presented to automatically extract, on a stride-by-stride basis, four consecutive fundamental events of walking, heel strike (HS), toe strike (TS), heel-off (HO ... [more ▼]

An original signal processing algorithm is presented to automatically extract, on a stride-by-stride basis, four consecutive fundamental events of walking, heel strike (HS), toe strike (TS), heel-off (HO), and toe-off (TO), from wireless accelerometers applied to the right and left foot. First, the signals recorded from heel and toe three-axis accelerometers are segmented providing heel and toe flat phases. Then, the four gait events are defined from these flat phases. The accelerometer-based event identification was validated in seven healthy volunteers and a total of 247 trials against reference data provided by a force plate, a kinematic 3D analysis system, and video camera. HS, TS, HO, and TO were detected with a temporal accuracy ± precision of 1.3 ms ± 7.2 ms, ‒4.2 ms ± 10.9 ms, ‒3.7 ms ± 14.5 ms, and ‒1.8 ms ± 11.8 ms, respectively, with the associated 95% confidence intervals ranging from ‒6.3 ms to 2.2 ms. It is concluded that the developed accelerometer-based method can accurately and precisely detect HS, TS, HO, and TO, and could thus be used for the ambulatory monitoring of gait features computed from these events when measured concurrently in both feet. [less ▲]

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See detailSegmentation of gait cycles using foot-mounted 3D accelerometers
Boutaayamou, Mohamed ULg; Bruls, Olivier ULg; Denoël, Vincent ULg et al

in Proceedings of the IEEE International Conference on 3D Imaging 2015 (2015)

We describe a new gait segmentation method based on the continuous wavelet transform to identify stride-by-stride gait cycles from measurements of foot-mounted three-dimensional (3D) accelerometers. The ... [more ▼]

We describe a new gait segmentation method based on the continuous wavelet transform to identify stride-by-stride gait cycles from measurements of foot-mounted three-dimensional (3D) accelerometers. The detection of such gait cycles is indeed a crucial step for an accurate extraction of relevant gait events such as heel strike, toe strike, heel-off, and toe-off. We demonstrate the ability of this segmentation method, used in conjunction with a validated extraction algorithm, to calculate the following gait (duration) parameters for each gait cycle during the gait of a healthy young subject and of an elderly subject with Parkinson’s disease (PD) in OFF and ON states: durations of (1) loading response, (2) mid-stance, (3) push-off, (4) stance, (5) swing, (6) stride, (7) step, and (8) double support phases. The experimental results show that the proposed method can extract relevant refined gait parameters to quantify subtle gait disturbances in subjects with PD. [less ▲]

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See detailContribution of a Trunk Accelerometer System to the Characterization of Gait in Patients With Mild-to-Moderate Parkinson’s Disease
Demonceau, Marie ULg; Donneau, Anne-Françoise ULg; CROISIER, Jean-Louis ULg et al

in IEEE Journal of Biomedical and Health Informatics (2015)

OBJECTIVE: Gait disturbances like shuffling and short steps are obvious at visual observation in patients with advanced Parkinson's disease (PD). However, quantitative methods are increasingly used to ... [more ▼]

OBJECTIVE: Gait disturbances like shuffling and short steps are obvious at visual observation in patients with advanced Parkinson's disease (PD). However, quantitative methods are increasingly used to evaluate the wide range of gait abnormalities that may occur over the disease course. The goal of this study was to test the ability of a trunk accelerometer system to quantify the effects of PD on several gait features when walking at self-selected speed. METHODS: We recruited 96 subjects split into three age-matched groups: 32 healthy controls (HC), 32 PD patients at Hoehn and Yahr stage < II (PD-1), and 32 patients at Hoehn & Yahr stage II-III (PD-2). The following outcomes were extracted from the signals of the tri-axial accelerometer worn on the lower back: stride length, cadence, regularity index, symmetry index and mechanical powers yielded in the cranial-caudal, antero-posterior and medial-lateral directions. Walking speed was measured using a stopwatch. RESULTS: beside other gait features, the PD-1 and the PD-2 groups showed significantly reduced stride length normalized to height (p<0.02) and symmetry index (p<0.009) in comparison to the HC. Regularity index was the only feature significantly decreased in the PD-2 group as compared with the two other groups (p<0.01). The clinical relevance of this finding was supported by significant correlations with mobility and gait scales (r is around -0.3; p<0.05). CONCLUSION: Gait quantified by a trunk accelerometer may provide clinically useful information for the screening and follow-up of PD patients. [less ▲]

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See detailAmbulatory system using wearable accelerometers for gait analysis in Parkinson’s disease
Boutaayamou, Mohamed ULg; Demonceau, Marie ULg; Schwartz, Cédric ULg et al

in Proceedings of the 14th Belgian Day on Biomedical Engineering (2015)

We describe a signal-processing algorithm for gait analysis in Parkinson’s disease (PD) using an ambulatory system with wearable accelerometers. This algorithm is versatile enough to detect, on a stride ... [more ▼]

We describe a signal-processing algorithm for gait analysis in Parkinson’s disease (PD) using an ambulatory system with wearable accelerometers. This algorithm is versatile enough to detect, on a stride-by-stride basis, refined gait parameters that quantify subtle gait disturbances in PD in a rater-independent way. [less ▲]

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See detailDevelopment and validation of a 3D kinematic-based method for determining gait events during overground walking
Boutaayamou, Mohamed ULg; Schwartz, Cédric ULg; Denoël, Vincent ULg et al

in IEEE International Conference on 3D Imaging (IC3D) (2014, December 09)

A new signal processing algorithm is developed for quantifying heel strike (HS) and toe-off (TO) event times solely from measured heel and toe coordinates during overground walking. It is based on a rough ... [more ▼]

A new signal processing algorithm is developed for quantifying heel strike (HS) and toe-off (TO) event times solely from measured heel and toe coordinates during overground walking. It is based on a rough estimation of relevant local 3D position signals. An original piecewise linear fitting method is applied to these local signals to accurately identify HS and TO times without the need of using arbitrary experimental coefficients. We validated the proposed method with nine healthy subjects and a total of 322 trials. The extracted temporal gait events were compared to reference data obtained from a force plate. HS and TO times were identified with a temporal accuracy ± precision of 0.3 ms ± 7.1 ms, and –2.8 ms ± 7.2 ms in comparison with reference data defined with a force threshold of 10 N. This algorithm improves the accuracy of the HS and TO detection. Furthermore, it can be used to perform stride-by-stride analysis during overground walking with only recorded heel and toe coordinates. [less ▲]

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See detailDesign and implementation of a T impedance matching network for the radiocommunication subsystem aboard the OUFTI-1 nanosatellite
Boutaayamou, Mohamed ULg; Crosset, Nicolas ULg; Werner, Xavier ULg et al

in Proceedings of the URSI Forum 2014 (2014, November 18)

We describe how we handled an unexpected impedance matching issue on the receiver side (at UHF) of the radiocommunication system aboard the OUFTI-1 nanosatellite of the University of Liège. Our approach ... [more ▼]

We describe how we handled an unexpected impedance matching issue on the receiver side (at UHF) of the radiocommunication system aboard the OUFTI-1 nanosatellite of the University of Liège. Our approach relied on a combination of novel analytical developments combined with experimentation. [less ▲]

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See detailValidation des paramètres de marche par un système accélérométrique (Locométrix*) à l'aide d'un système opto-électronique 3D (Coda Motion )
GILLAIN, Sophie ULg; Schwartz, Cédric ULg; Boutaayamou, Mohamed ULg et al

in Gériatrie et Psychologie Neuropsychiatrie du Vieillissement (2014), 12(supplément 3),

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See detailDesign and fabrication of an electrode array sensor for probing the electric potential distribution at the mesoscopic scale in antistatic felts
Boutaayamou, Mohamed ULg; Lemaire, Philippe; Vanderheyden, Benoît ULg et al

in Measurement Science and Technology (2014), 25

We present an original voltage probe design for measuring the electric potential distribution at the mesoscopic scale (i.e., 1 mm–1 cm) in antistatic felts. The felts are composed of a mixture of non ... [more ▼]

We present an original voltage probe design for measuring the electric potential distribution at the mesoscopic scale (i.e., 1 mm–1 cm) in antistatic felts. The felts are composed of a mixture of non-conductive and metallic fibers and exhibit complex nonlinear electric behavior—including possibly nonlinearity and hysteresis effects—which may be due to localized electrical or electromechanical phenomena. The sensor consists of an array of 8 × 9 needle electrodes (phgr 160 µm at the shaft and less than phgr 50 µm toward the apex), which are mechanically maintained at fixed relative positions while their tips are inserted inside the fabric of the sample. The interelectrode distance is 1.5 mm and the overall active area is 12 × 12 mm². The electrical insulation resistance for nearest neighbor pairs of electrodes was found to be larger than 860 GΩ, thus making the sensor suitable for measuring antistatic felts with an electric resistance that typically does not exceed a few GΩ. The sensor was successfully used for measuring the distribution of the electric potential in a polyester fabric subjected to voltages of up to 6.2 kV, and in a sample containing 2% in weight of metallic fibers, demonstrating the presence of irreversible changes in that felt sample (i.e., with conductive fibers) at high voltages. It is concluded that the developed probe voltage is a promising technique that could be used for the assessment of the conduction mechanisms in the antistatic materials at the mesoscopic scale. [less ▲]

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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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