当前位置： SCI文献检索 > IEEE Journal of Biomedical and Health Informatics期刊下所有文献 > Contribution of a Trunk Accelerometer System to the Characterization of Gait in Patients With Mild-to-Moderate Parkinson's Disease.

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

Abstract：

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 and Yahr stage II-III (PD-2). The following outcomes were extracted from the signals of the triaxial accelerometer worn on the lower back: stride length, cadence, regularity index, symmetry index, and mechanical powers yielded in the cranial-caudal, anteroposterior, and medial-lateral directions. Walking speed was measured using a stopwatch. RESULTS:Besides 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.

journal_name

IEEE J Biomed Health Inform

journal_title

IEEE journal of biomedical and health informatics

authors

Demonceau M,Donneau AF,Croisier JL,Skawiniak E,Boutaayamou M,Maquet D,Garraux G

doi

10.1109/JBHI.2015.2469540

subject

Has Abstract

pub_date

2015-11-01 00:00:00

pages

1803-8

issue

6

eissn

2168-2194

issn

2168-2208

journal_volume

19

pub_type

杂志文章

相关文献

IEEE Journal of Biomedical and Health Informatics文献大全
  • Unsupervised Bayesian Inference to Fuse Biosignal Sensory Estimates for Personalizing Care.

    abstract：:The role of sensing technologies, such as wearables, in delivering precision care is becoming widely acceptable. Given the very large quantities of sensor data that rapidly accumulate, there is a need to employ automated algorithms to label biosignal sensor data. In many real-life clinical applications, no such expert...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2018.2820054

    authors： Zhu T,Pimentel MAF,Clifford GD,Clifton DA

    更新日期：2019-01-01 00:00:00

  • A Framework for Classifying Online Mental Health-Related Communities With an Interest in Depression.

    abstract：:Mental illness has a deep impact on individuals, families, and by extension, society as a whole. Social networks allow individuals with mental disorders to communicate with others sufferers via online communities, providing an invaluable resource for studies on textual signs of psychological health problems. Mental di...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2016.2543741

    authors： Saha B,Nguyen T,Phung D,Venkatesh S

    更新日期：2016-07-01 00:00:00

  • Data mining in bone marrow transplant records to identify patients with high odds of survival.

    abstract：:Patients undergoing a bone marrow stem cell transplant (BMT) face various risk factors. Analyzing data from past transplants could enhance the understanding of the factors influencing success. Records up to 120 measurements per transplant procedure from 1751 patients undergoing BMT were collected (Shariati Hospital). ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2013.2274733

    authors： Taati B,Snoek J,Aleman D,Ghavamzadeh A

    更新日期：2014-01-01 00:00:00

  • Q-Rank: Reinforcement Learning for Recommending Algorithms to Predict Drug Sensitivity to Cancer Therapy.

    abstract：:In personalized medicine, a challenging task is to identify the most effective treatment for a patient. In oncology, several computational models have been developed to predict the response of drugs to therapy. However, the performance of these models depends on multiple factors. This paper presents a new approach, ca...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3004663

    authors： Daoud S,Mdhaffar A,Jmaiel M,Freisleben B

    更新日期：2020-11-01 00:00:00

  • Blind end-member and abundance extraction for multispectral fluorescence lifetime imaging microscopy data.

    abstract：:This paper proposes a new blind end-member and abundance extraction (BEAE) method for multispectral fluorescence lifetime imaging microscopy (m-FLIM) data. The chemometrical analysis relies on an iterative estimation of the fluorescence decay end-members and their abundances. The proposed method is based on a linear m...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2013.2279335

    authors： Gutierrez-Navarro O,Campos-Delgado DU,Arce-Santana ER,Mendez MO,Jo JA

    更新日期：2014-03-01 00:00:00

  • Improving compliance in remote healthcare systems through smartphone battery optimization.

    abstract：:Remote health monitoring (RHM) has emerged as a solution to help reduce the cost burden of unhealthy lifestyles and aging populations. Enhancing compliance to prescribed medical regimens is an essential challenge to many systems, even those using smartphone technology. In this paper, we provide a technique to improve ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 临床试验,杂志文章

    doi：10.1109/JBHI.2014.2329712

    authors： Alshurafa N,Eastwood JA,Nyamathi S,Liu JJ,Xu W,Ghasemzadeh H,Pourhomayoun M,Sarrafzadeh M

    更新日期：2015-01-01 00:00:00

  • Assessment of Signal Processing Methods for Measuring the Respiratory Rate in the Neonatal Intensive Care Unit.

    abstract：:Knowledge of the pathological instabilities in the breathing pattern can provide valuable insights into the cardiorespiratory status of the critically-ill infant as well as their maturation level. This paper is concerned with the measurement of respiratory rate in premature infants. We compare the rates estimated from...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2898273

    authors： Jorge J,Villarroel M,Chaichulee S,Green G,McCormick K,Tarassenko L

    更新日期：2019-11-01 00:00:00

  • A Deep Learning Based Unsupervised Method to Impute Missing Values in Patient Records for Improved Management of Cardiovascular Patients.

    abstract：:Physicians increasingly depend on electronic health records (EHRs) to manage patients. However, many patient records have substantial missing values that pose a fundamental challenge to their clinical use. To address this prevailing challenge, we propose an unsupervised deep-learning method that can facilitate physici...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3033323

    authors： Xu D,Sheng JQ,Hu PJ,Huang TS,Hsu CC

    更新日期：2020-10-23 00:00:00

  • 2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-center Study.

    abstract：OBJECTIVE:Radiomics, an emerging tool for medical image analysis, is potential towards precisely characterizing gastric cancer (GC). Whether using one-slice 2D annotation or whole-volume 3D annotation remains a long-time debate, especially for heterogeneous GC. We comprehensively compared 2D and 3D radiomic features' r...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3002805

    authors： Meng L,Dong D,Chen X,Fang M,Wang R,Li J,Liu Z,Tian J

    更新日期：2020-06-16 00:00:00

  • Toward a Wirelessly Powered On-Lens Intraocular Pressure Monitoring System.

    abstract：:This paper presents a wireless on-lens intraocular pressure monitoring system, comprising a capacitance-to-digital converter and a wirelessly powered radio-frequency identification (RFID)-compatible communication system, for sensor control and data communication. The capacitive sensor was embedded on a soft contact le...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2016.2594058

    authors： Chiou JC,Hsu SH,Liao YT,Huang YC,Yeh GT,Kuei CK,Dai KS

    更新日期：2016-09-01 00:00:00

  • 40-Hz ASSR for Measuring Depth of Anaesthesia During Induction Phase.

    abstract：:This paper proposes an anaesthesia monitoring system that accurately measures the depth of anaesthesia through 40-Hz auditory steady-state response. With accurate and fast depth of anaesthesia measuring, the monitor can reduce the incidence of awareness during surgical operation. The proposed denoising method for extr...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2778140

    authors： Haghighi SJ,Komeili M,Hatzinakos D,Beheiry HE

    更新日期：2018-11-01 00:00:00

  • Sleeve for Knee Angle Monitoring: An IMU-POF Sensor Fusion System.

    abstract：:The knee flexion-extension angle is an important variable to be monitored in various clinical scenarios, for example, during physical rehabilitation assessment. The purpose of this work is to develop and validate a sensor fusion system based on a knee sleeve for monitoring of physical therapy. The system consists of m...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2988360

    authors： Vargas Valencia LS,B A Schneider F,Leal-Junior A,Caicedo-Rodriguez P,Sierra-Arevalo WA,Rodriguez-Cheu LE,Bastos-Filho TF,Frizera A

    更新日期：2020-04-20 00:00:00

  • A method of detecting heartbeat locations in the ballistocardiographic signal from the fiber-optic vital signs sensor.

    abstract：:We present a flexible, easy-to-expand digital signal processing method for detecting heart rate (HR) for cardiac vibration signals of fiber Bragg grating (FBG) sensor. The FBG-based method of measuring HR is possible to use during the magnetic resonance imaging procedure, which is its unique advantage. Our goal was to...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2392796

    authors： Krej M,Dziuda L,Skibniewski FW

    更新日期：2015-07-01 00:00:00

  • Advanced Insulin Bolus Advisor Based on Run-To-Run Control and Case-Based Reasoning.

    abstract：:This paper presents an advanced insulin bolus advisor for people with diabetes on multiple daily injections or insulin pump therapy. The proposed system, which runs on a smartphone, keeps the simplicity of a standard bolus calculator while enhancing its performance by providing more adaptability and flexibility. This ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2331896

    authors： Herrero P,Pesl P,Reddy M,Oliver N,Georgiou P,Toumazou C

    更新日期：2015-05-01 00:00:00

  • The technologically integrated oncosimulator: combining multiscale cancer modeling with information technology in the in silico oncology context.

    abstract：:This paper outlines the major components and function of the technologically integrated oncosimulator developed primarily within the Advancing Clinico Genomic Trials on Cancer (ACGT) project. The Oncosimulator is defined as an information technology system simulating in vivo tumor response to therapeutic modalities wi...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2013.2284276

    authors： Stamatakos G,Dionysiou D,Lunzer A,Belleman R,Kolokotroni E,Georgiadi E,Erdt M,Pukacki J,Rüeping S,Giatili S,d'Onofrio A,Sfakianakis S,Marias K,Desmedt C,Tsiknakis M,Graf N

    更新日期：2014-05-01 00:00:00

  • Segmentation and Measurement of Chronic Wounds for Bioprinting.

    abstract：OBJECTIVE:to provide a proof-of-concept tool for segmenting chronic wounds and transmitting the results as instructions and coordinates to a bioprinter robot and thus facilitate the treatment of chronic wounds. METHODS:several segmentation methods used for measuring wound geometry, including edge-detection and morphol...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2743526

    authors： Gholami P,Ahmadi-Pajouh MA,Abolftahi N,Hamarneh G,Kayvanrad M,Gholami P,Ahmadi-Pajouh MA,Abolftahi N,Hamarneh G,Kayvanrad M

    更新日期：2018-07-01 00:00:00

  • Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images.

    abstract：:Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the fol...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2014.2304179

    authors： Seguí S,Drozdzal M,Zaytseva E,Malagelada C,Azpiroz F,Radeva P,Vitrià J

    更新日期：2014-11-01 00:00:00

  • Attention-Guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association Using Volumetric Images.

    abstract：:The direct analysis of 3D Optical Coherence Tomography (OCT) volumes enables deep learning models (DL) to learn spatial structural information and discover new bio-markers that are relevant to glaucoma. Downsampling 3D input volumes is the state-of-art solution to accommodate for the limited number of training volumes...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3001019

    authors： George Y,Antony BJ,Ishikawa H,Wollstein G,Schuman JS,Garnavi R

    更新日期：2020-12-01 00:00:00

  • Detection and Control of Unannounced Exercise in the Artificial Pancreas Without Additional Physiological Signals.

    abstract：:The purpose of this study was to develop an algorithm that detects aerobic exercise and triggers disturbance rejection actions to prevent exercise-induced hypoglycemia. This approach can provide a solution to poor glycemic control during and after aerobic exercise, a major hindrance in the participation of exercise by...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2898558

    authors： Ramkissoon CM,Bertachi A,Beneyto A,Bondia J,Vehi J

    更新日期：2020-01-01 00:00:00

  • Robotic-Assisted Needle Steering Around Anatomical Obstacles Using Notched Steerable Needles.

    abstract：:Robotic-assisted needle steering can enhance the accuracy of needle-based interventions. Application of current needle steering techniques are restricted by the limited deflection curvature of needles. Here, a novel steerable needle with improved curvature is developed and used with an online motion planner to steer t...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2017.2780192

    authors： Khadem M,Rossa C,Usmani N,Sloboda RS,Tavakoli M

    更新日期：2018-11-01 00:00:00

  • A joint FED watermarking system using spatial fusion for verifying the security issues of teleradiology.

    abstract：:Teleradiology allows transmission of medical images for clinical data interpretation to provide improved e-health care access, delivery, and standards. The remote transmission raises various ethical and legal issues like image retention, fraud, privacy, malpractice liability, etc. A joint FED watermarking system means...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2013.2281322

    authors： Viswanathan P,Krishna PV

    更新日期：2014-05-01 00:00:00

  • Atrial Fibrillation Detection During Sepsis: Study on MIMIC III ICU Data.

    abstract：:Sepsis is defined by life-threatening organ dysfunction during infection and is one of the leading causes of critical illness. During sepsis, there is high risk that new-onset of atrial fibrillation (AF) can occur, which is associated with significant morbidity and mortality. As a result, computer aided automated and ...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2995139

    authors： Bashar SK,Hossain MB,Ding E,Walkey AJ,McManus DD,Chon KH

    更新日期：2020-11-01 00:00:00

  • Length-of-Stay Prediction for Pediatric Patients With Respiratory Diseases Using Decision Tree Methods.

    abstract：:Accurate prediction of a patient's length-of-stay (LOS) in the hospital enables an efficient and effective management of hospital beds. This paper studies LOS prediction for pediatric patients with respiratory diseases using three decision tree methods: Bagging, Adaboost, and Random forest. A data set of 11,206 record...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2973285

    authors： Ma F,Yu L,Ye L,Yao DD,Zhuang W

    更新日期：2020-09-01 00:00:00

  • AW-SDRLSE: Adaptive Weighting and Scalable Distance Regularized Level Set Evolution for Lymphoma Segmentation on PET Images.

    abstract：:Accurate lymphoma segmentation on Positron Emission Tomography (PET) images is of great importance for medical diagnoses, such as for distinguishing benign and malignant. To this end, this paper proposes an adaptive weighting and scalable distance regularized level set evolution (AW-SDRLSE) method for delineating lymp...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.3017546

    authors： Li S,Jiang H,Li H,Yao YD

    更新日期：2020-08-25 00:00:00

  • A Realistic Framework for Investigating Decision Making in the Brain With High Spatiotemporal Resolution Using Simultaneous EEG/fMRI and Joint ICA.

    abstract：:Human decision making is a multidimensional construct, driven by a complex interplay between external factors, internal biases, and computational capacity constraints. Here, we propose a layered approach to experimental design in which multiple tasks-from simple to complex-with additional layers of complexity introduc...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2016.2590434

    authors： Kyathanahally SP,Franco-Watkins A,Zhang X,Calhoun VD,Deshpande G

    更新日期：2017-05-01 00:00:00

  • Neuroimaging Retrieval via Adaptive Ensemble Manifold Learning for Brain Disease Diagnosis.

    abstract：:Alzheimer's disease (AD) is a neurodegenerative and non-curable disease, with serious cognitive impairment, such as dementia. Clinically, it is critical to study the disease with multi-source data in order to capture a global picture of it. In this respect, an adaptive ensemble manifold learning (AEML) algorithm is pr...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2018.2872581

    authors： Lei B,Yang P,Zhuo Y,Zhou F,Ni D,Chen S,Xiao X,Wang T

    更新日期：2019-07-01 00:00:00

  • Bi-Frequency Symmetry Difference EIT-Feasibility and Limitations of Application to Stroke Diagnosis.

    abstract：OBJECTIVE:Bi-Frequency Symmetry Difference (BFSD)-EIT can detect, localize and identify unilateral perturbations in symmetric scenes. Here, we test the viability and robustness of BFSD-EIT in stroke diagnosis. METHODS:A realistic 4-layer Finite Element Method (FEM) head model with and without bleed and clot lesions is...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2019.2960862

    authors： McDermott B,O'Halloran M,Avery J,Porter E

    更新日期：2020-08-01 00:00:00

  • The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition.

    abstract：:The recorded electroencephalography (EEG) signals are usually contaminated by electrooculography (EOG) artifacts. In this paper, by using independent component analysis (ICA) and multivariate empirical mode decomposition (MEMD), the ICA-based MEMD method was proposed to remove EOG artifacts (EOAs) from multichannel EE...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2015.2450196

    authors： Wang G,Teng C,Li K,Zhang Z,Yan X

    更新日期：2016-09-01 00:00:00

  • Biologically Inspired QuadTree Color Detection in Dermoscopy Images of Melanoma.

    abstract：:This paper presents a QuadTree-based melanoma detection system inspired by dermatologists' color perception. Clinical color assessment in dermoscopy images is challenging because of subtle differences in shades, location-dependent color information, poor color contrast, and wide variation among images of the same clas...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2018.2841428

    authors： Sabbaghi Mahmouei S,Aldeen M,Stoecker WV,Garnavi R

    更新日期：2019-03-01 00:00:00

  • ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach.

    abstract：:Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy and glaucoma. Commonly used modalities in diagnosis of these diseases are fundus photography, scanning laser ophthalmoscope (SLO) and fluor...

    journal_title：IEEE journal of biomedical and health informatics

    pub_type： 杂志文章

    doi：10.1109/JBHI.2020.2999257

    authors： Rodrigues EO,Conci A,Liatsis P

    更新日期：2020-12-01 00:00:00