Contribution of a Trunk Accelerometer System to the Characterization of Gait in Patients With Mild-to-Moderate Parkinson's Disease

Demonceau, Marie; Donneau, Anne‐Françoise; Croisier, Jean-Louis; Skawiniak, Eva; Boutaayamou, Mohamed; Maquet, Didier; Garraux, Gaëtan

doi:10.1109/jbhi.2015.2469540

Cited by 35 publications

(29 citation statements)

References 32 publications

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“…Only one work (Salarian et al, 2009 ) was focused on turning; it recognized differences between early PwPD and HC with excellent sensitivity and reliability thanks to the automatic detection of all turns. The majority of the works compared the performances of a group composed of PwPD and a group of control subjects (Barth et al, 2013 ; Palmerini et al, 2013 ; Arora et al, 2014 ; Oung et al, 2015 ; Parisi et al, 2015 ), and showed that the second group had better results in terms of time of execution, speed (Horak et al, 2016 ), regularity, cadence, symmetry, stride length (Demonceau et al, 2015 ), amplitude, and slope (Weiss et al, 2011 ). Others implemented multi-class classification to distinguish among HC, PwPD without gait disturbance, and PwPD with gait disturbance (Tien et al, 2010 ) or compared the performance of HC, PwPD, and subjects with dementia (Yoneyama et al, 2016 ).…”

Section: Resultsmentioning

confidence: 99%

“…In several studies, moderate patients (e.g., HY = 2/3, Palmerini et al, 2013 ; Yoneyama et al, 2013 ; Sejdić et al, 2016 ) were involved, so the difference in performance between PwPD and HC are easily identifiable. The recruitment of PwPD in the first stage of the disease (i.e., HY = 1) should be primarily investigated to demonstrate the accuracy and the objectivity of the technological solutions with respect to the traditional clinical evaluations (Demonceau et al, 2015 ), aiming to achieve early diagnosis of the pathology (Barth et al, 2011 ). Many gait analysis protocols have been developed to complete the medical exam of PD patients, but the optimal method remains under debate (Demonceau et al, 2015 ).…”

Section: Resultsmentioning

confidence: 99%

“…The recruitment of PwPD in the first stage of the disease (i.e., HY = 1) should be primarily investigated to demonstrate the accuracy and the objectivity of the technological solutions with respect to the traditional clinical evaluations (Demonceau et al, 2015 ), aiming to achieve early diagnosis of the pathology (Barth et al, 2011 ). Many gait analysis protocols have been developed to complete the medical exam of PD patients, but the optimal method remains under debate (Demonceau et al, 2015 ). Regardless, the use of inertial sensors placed on different parts of the body seems to be a promising method for objective estimation of the parameters of the gait (Barth et al, 2013 ; Del Din et al, 2016 ; Ferrari et al, 2016 ).…”

Section: Resultsmentioning

confidence: 99%

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How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review

Maremmani²,

2017

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Background: Parkinson's disease (PD) is a common and disabling pathology that is characterized by both motor and non-motor symptoms and affects millions of people worldwide. The disease significantly affects quality of life of those affected. Many works in literature discuss the effects of the disease. The most promising trends involve sensor devices, which are low cost, low power, unobtrusive, and accurate in the measurements, for monitoring and managing the pathology. Objectives: This review focuses on wearable devices for PD applications and identifies five main fields: early diagnosis, tremor, body motion analysis, motor fluctuations (ON–OFF phases), and home and long-term monitoring. The concept is to obtain an overview of the pathology at each stage of development, from the beginning of the disease to consider early symptoms, during disease progression with analysis of the most common disorders, and including management of the most complicated situations (i.e., motor fluctuations and long-term remote monitoring). Data sources: The research was conducted within three databases: IEEE Xplore®, Science Direct®, and PubMed Central®, between January 2006 and December 2016. Study eligibility criteria: Since 1,429 articles were found, accurate definition of the exclusion criteria and selection strategy allowed identification of the most relevant papers. Results: Finally, 136 papers were fully evaluated and included in this review, allowing a wide overview of wearable devices for the management of Parkinson's disease.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review

Maremmani²,

2017

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“…Other studies of interest include [24,26,29], which are quite different compared to the other studies reviewed in this section, as they do not aim to extract standard gait metrics. However, they are worthy of attention since they aim to extract balance and symmetry-related upper-body features from the raw data of sensors placed on the trunk.…”

Section: Related Work On Gait Analysis With Imusmentioning

confidence: 99%

Inertial Sensor-Based Robust Gait Analysis in Non-Hospital Settings for Neurological Disorders

Tunca

Pehlivan

Ak³

et al. 2017

Sensors

126

118

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The gold standards for gait analysis are instrumented walkways and marker-based motion capture systems, which require costly infrastructure and are only available in hospitals and specialized gait clinics. Even though the completeness and the accuracy of these systems are unquestionable, a mobile and pervasive gait analysis alternative suitable for non-hospital settings is a clinical necessity. Using inertial sensors for gait analysis has been well explored in the literature with promising results. However, the majority of the existing work does not consider realistic conditions where data collection and sensor placement imperfections are imminent. Moreover, some of the underlying assumptions of the existing work are not compatible with pathological gait, decreasing the accuracy. To overcome these challenges, we propose a foot-mounted inertial sensor-based gait analysis system that extends the well-established zero-velocity update and Kalman filtering methodology. Our system copes with various cases of data collection difficulties and relaxes some of the assumptions invalid for pathological gait (e.g., the assumption of observing a heel strike during a gait cycle). The system is able to extract a rich set of standard gait metrics, including stride length, cadence, cycle time, stance time, swing time, stance ratio, speed, maximum/minimum clearance and turning rate. We validated the spatio-temporal accuracy of the proposed system by comparing the stride length and swing time output with an IR depth-camera-based reference system on a dataset comprised of 22 subjects. Furthermore, to highlight the clinical applicability of the system, we present a clinical discussion of the extracted metrics on a disjoint dataset of 17 subjects with various neurological conditions.

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“…[32] reports the usage of accelerometers located at a patient's both wrists and the left ankle to monitor the Parkinson's disease. In [33], the same disease is monitored by using accelerometers installed at the trunk of a patient. For sports applications, [34] presents a motions tracking system based on inertial sensors placed at the hip, leg and foot.…”

Section: Selection Of Antenna Locations and Measurement Implementationmentioning

confidence: 99%

Categorized Uwb on-Body Radio Channel Modeling for Wbans

Kumpuniemi¹,

Hämäläinen²,

Yazdandoost³

et al. 2016

PIER B

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Abstract-A categorized radio channel modeling for wireless ultra-wideband on-body body area networks is discussed. Measurements in an anechoic chamber at fourteen antenna locations are conducted in a 2-8 GHz band. The dipole and double loop antenna types are used. Six link classes are formed based on the antenna spots on the torso, head or limb. The limb-limb and the head-limb links have the lowest and highest path losses, respectively. The head-limb links have the shortest channel impulse responses (CIRs) and limb-limb links the longest ones. The CIR amplitudes follow the inverse Gaussian distribution. The tap indexes and the total excess delays are modeled with the negative binomial distribution. In most cases, the CIRs decay faster for the dipole. Otherwise no major differences exist between the antennas.

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Contribution of a Trunk Accelerometer System to the Characterization of Gait in Patients With Mild-to-Moderate Parkinson's Disease

Abstract: Gait quantified by a trunk accelerometer may provide clinically useful information for the screening and follow-up of PD patients.

Cited by 35 publications

References 32 publications

How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review

How Wearable Sensors Can Support Parkinson's Disease Diagnosis and Treatment: A Systematic Review

Inertial Sensor-Based Robust Gait Analysis in Non-Hospital Settings for Neurological Disorders

Categorized Uwb on-Body Radio Channel Modeling for Wbans

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