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Accelerometry and parkinson's disease

Sarah J Ozinga, Susan M Linder, Jay L Alberts
OBJECTIVE: To determine the accuracy of inertial measurement unit data from a mobile device using the mobile device relative to posturography to quantify postural stability in individuals with Parkinson's disease (PD). DESIGN: Criterion standard. SETTING: Motor control laboratory at Cleveland Clinic. PARTICIPANTS: Fourteen mild to moderate individuals with PD and 14 healthy age-matched community dwelling controls completed the project...
September 23, 2016: Archives of Physical Medicine and Rehabilitation
Michelle Braybrook, Sam O'Connor, Philip Churchward, Thushara Perera, Parisa Farzanehfar, Malcolm Horne
BACKGROUND: While tremor in Parkinson's Disease (PD) can be characterised in the consulting room, its relationship to treatment and fluctuations can be clinically helpful. OBJECTIVE: To develop an ambulatory assessment of tremor of PD. METHODS: Accelerometry data was collected using the Parkinson's KinetiGraph System (PKG, Global Kinetics). An algorithm was developed, which could successfully distinguish been subjects with a resting or postural tremor that involved the wrist whose frequency was greater than 3 Hz...
October 19, 2016: Journal of Parkinson's Disease
Alexander P Turner, Michael A Lones, Martin A Trefzer, Stephen L Smith, Stuart Jamieson, Jane E Alty, Jeremy Cosgrove, Andy M Tyrrell
Levodopa is a drug that is commonly used to treat movement disorders associated with Parkinson's disease. Its dosage requires careful monitoring, since the required amount changes over time, and excess dosage can lead to muscle spasms known as levodopa-induced dyskinesia. In this work, we investigate the potential for using epiNet, a novel artificial gene regulatory network, as a classifier for monitoring accelerometry time series data collected from patients undergoing levodopa therapy. We also consider how dynamical analysis of epiNet classifiers and their transitions between different states can highlight clinically useful information which is not available through more conventional data mining techniques...
August 2016: Bio Systems
Ervin Sejdić, Kristin A Lowry, Jennica Bellanca, Subashan Perera, Mark S Redfern, Jennifer S Brach
OBJECTIVE: Evaluating stride events can be valuable for understanding the changes in walking due to aging and neurological diseases. However, creating the time series necessary for this analysis can be cumbersome. In particular, finding heel contact and toe-off events which define the gait cycles accurately are difficult. METHOD: We proposed a method to extract stride cycle events from tri-axial accelerometry signals. We validated our method via data collected from 14 healthy controls, 10 participants with Parkinson's disease and 11 participants with peripheral neuropathy...
2016: IEEE Journal of Translational Engineering in Health and Medicine
Nivedita Khobragade, Daniel Graupe, Daniela Tuninetti
This paper describes the application of the LAMSTAR (LArge Memory STorage and Retrieval) neural network for prediction of onset of tremor in Parkinson's disease (PD) patients to allow for on-off adaptive control of Deep Brain Stimulation (DBS). Currently, the therapeutic treatment of PD by DBS is an open-loop system where continuous stimulation is applied to a target area in the brain. This work demonstrates a fully automated closed-loop DBS system so that stimulation can be applied on-demand only when needed to treat PD symptoms...
2015: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Mitsuru Yoneyama, Hiroshi Mitoma, Nobuo Sanjo, Maya Higuma, Hiroo Terashi, Takanori Yokota
Accelerometry-based gait analysis is a promising approach in obtaining insightful information on the gait characteristics of patients with neurological disorders such as dementia and Parkinson's disease (PD). In order to improve its practical use outside the laboratory or hospital, it is required to design new metrics capable of quantifying ambulatory gait and their extraction procedures from long-term acceleration data. This paper presents a gait analysis method developed for such a purpose. Our system is based on a single trunk-mounted accelerometer and analytical algorithm for the assessment of gait behavior that may be context dependent...
August 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Thushara Perera, Shivanthan A C Yohanandan, Hugh J McDermott
Since the advent of electromyogram recording, precise measures of tremor and gait have been used to study movement disorders such as Parkinson's disease. Now, a wide range of accelerometers and other motion-tracking technologies exist to better inform researchers and clinicians, yet such systems are rarely tested for accuracy or suitability before use. Our inexpensive test-rig can produce sinusoidal displacements using a simple cantilever system driven by a subwoofer. Controlled sinusoids were generated using computer software, and the displacement amplitudes of the test-rig were verified with fiducial marker tracking...
March 2016: Medical & Biological Engineering & Computing
Alexandre Millecamps, Kristin A Lowry, Jennifer S Brach, Subashan Perera, Mark S Redfern, Ervin Sejdić
Gait accelerometry is an important approach for gait assessment. Previous contributions have adopted various pre-processing approaches for gait accelerometry signals, but none have thoroughly investigated the effects of such pre-processing operations on the obtained results. Therefore, this paper investigated the influence of pre-processing operations on signal features extracted from gait accelerometry signals. These signals were collected from 35 participants aged over 65years: 14 of them were healthy controls (HC), 10 had Parkinson׳s disease (PD) and 11 had peripheral neuropathy (PN)...
July 2015: Computers in Biology and Medicine
Malcolm K Horne, Sarah McGregor, Filip Bergquist
INTRODUCTION: Establishing the presence and severity of fluctuations is important in managing Parkinson's Disease yet there is no reliable, objective means of doing this. In this study we have evaluated a Fluctuation Score derived from variations in dyskinesia and bradykinesia scores produced by an accelerometry based system. METHODS: The Fluctuation Score was produced by summing the interquartile range of bradykinesia scores and dyskinesia scores produced every 2 minutes between 0900-1800 for at least 6 days by the accelerometry based system and expressing it as an algorithm...
2015: PloS One
Silvia Din, Alan Godfrey, Lynn Rochester
Measurement of gait is becoming important as a tool to identify disease and disease progression, yet to date its application is limited largely to specialist centres. Wearable devices enables gait to be measured in naturalistic environments however questions remain regarding validity. Previous research suggests that when compared with a laboratory reference, measurement accuracy is acceptable for mean but not variability or asymmetry gait characteristics. Some fundamental reasons for this have been presented (e...
April 2, 2015: IEEE Journal of Biomedical and Health Informatics
Bryan Lieber, Blake E S Taylor, Geoff Appelboom, Guy McKhann, E Sander Connolly
Patients with Parkinson disease (PD) often suffer from a resting tremor, bradykinesia, rigidity, postural instability, and gait difficulty. Determining a patient's candidacy for deep-brain stimulation (DBS) surgery and tracking their clinical response postoperatively requires that the frequency, duration, and severity of these symptoms be characterized in detail. Conventional means of assessing these symptoms, however, rely heavily on patient self-reporting, which often fails to provide the necessary level of detail...
August 2015: World Neurosurgery
John-Stuart Brittain, Hayriye Cagnan, Arpan R Mehta, Tabish A Saifee, Mark J Edwards, Peter Brown
Parkinson's disease (PD) and essential tremor (ET) are the two most common movement disorders. Both have been associated with similar patterns of network activation leading to the suggestion that they may result from similar network dysfunction, specifically involving the cerebellum. Here, we demonstrate that parkinsonian tremors and ETs result from distinct patterns of interactions between neural oscillators. These patterns are reflected in the tremors' derived frequency tolerance, a novel measure readily attainable from bedside accelerometry...
January 14, 2015: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
A M Ardi Handojoseno, James M Shine, Tuan N Nguyen, Yvonne Tran, Simon J G Lewis, Hung T Nguyen
Freezing of Gait (FOG) is a common symptom in the advanced stages of Parkinson's disease (PD), which significantly affects patients' quality of life. Treatment options offer limited benefit and there are currently no mechanisms able to effectively detect FOG before it occurs, allowing time for a sufferer to avert a freezing episode. Electroencephalography (EEG) offers a novel technique that may be able to address this problem. In this paper, we investigated the univariate and multivariate EEG features determined by both Fourier and wavelet analysis in the confirmation and prediction of FOG...
September 2015: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Daryl J Wile, Ranjit Ranawaya, Zelma H T Kiss
BACKGROUND: Distinguishing the postural re-emergent tremor of Parkinson disease from essential tremor can be difficult clinically. Use of accelerometry to aid diagnosis is limited to laboratory settings. We sought to record and differentiate these tremors using a smart watch device in an outpatient clinic. NEW METHOD: 41 patients were enrolled. Recordings were made with a smart watch device on the predominantly affected hand (all patients), and simultaneously with an analog accelerometer (10 patients) with hands at rest and outstretched...
June 15, 2014: Journal of Neuroscience Methods
Mitsuru Yoneyama, Yasuyuki Okuma, Hiroya Utsumi, Hiroo Terashi, Hiroshi Mitoma
Turnover is a typical intermittent body movement while asleep. Exploring its behavior may provide insights into the mechanisms and management of sleep. However, little is understood about the dynamic nature of turnover in healthy humans and how it can be modified in disease. Here we present a detailed analysis of turnover signals that are collected by accelerometry from healthy elderly subjects and age-matched patients with neurodegenerative disorders such as Parkinson's disease. In healthy subjects, the time intervals between consecutive turnover events exhibit a well-separated bimodal distribution with one mode at ⩽10 s and the other at ⩾100 s, whereas such bimodality tends to disappear in neurodegenerative patients...
March 2014: Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
Ariane Keitel, Stefano Ferrea, Martin Südmeyer, Alfons Schnitzler, Lars Wojtecki
Expectation contributes to placebo and nocebo responses in Parkinson's disease (PD). While there is evidence for expectation-induced modulations of bradykinesia, little is known about the impact of expectation on resting tremor. Subthalamic nucleus (STN) deep brain stimulation (DBS) improves cardinal PD motor symptoms including tremor whereas impairment of verbal fluency (VF) has been observed as a potential side-effect. Here we investigated how expectation modulates the effect of STN-DBS on resting tremor and its interaction with VF...
2013: PloS One
Brandon D Swan, Warren M Grill, Dennis A Turner
BACKGROUND: Direct testing of deep brain stimulation (DBS) mechanisms in humans is needed to assess therapy and to understand stimulation effects. OBJECTIVE: We developed an innovative paradigm for investigation of DBS on human movement disorders. Temporary connection to the DBS electrode during implantable pulse generator (IPG) replacement permitted analysis of novel patterns of stimulation on motor symptoms, which could enhance efficacy and improve battery life...
July 2014: Neuromodulation: Journal of the International Neuromodulation Society
Paula Faria, Miguel Patrício, Gregor Philipiak, Francisco Caramelo, Cristina Januário, António Freire, Miguel Castelo-Branco
Understanding the neurobiological mechanisms underlying different types of tremor and the altered functional connectivity of the involved areas is a timely goal in clinical neuroscience. If successful, this quest may open new perspectives on how to achieve tremor modulation, which is notably relevant, in Parkinson's disease (PD). Tremor can be characterized by simple parameters such as frequency and amplitude. It is therefore prone to be objectively targeted by neuromodulation and quantitatively investigated using multimodal techniques, such as, accelerometry, EMG and functional Magnetic Resonance Imaging (fMRI)...
2013: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abdulnasir Hossen
BACKGROUND: Essential tremor (ET) and the tremor in Parkinson's disease (PD) are the two most common pathological tremor with a certain overlap in the clinical presentation. OBJECTIVE: The main purpose of this work is to use an artificial neural network to select the best features and to discriminate between the two types of tremors using spectral analysis of tremor time-series recorded by accelerometry and surface EMG signals. METHODS: The Soft-Decision wavelet-based technique is to be used in this work in order to obtain a 16 bands approximate spectral representation of both accelerometer and two EMG signals of two sets of data (training and test)...
2013: Technology and Health Care: Official Journal of the European Society for Engineering and Medicine
Mitsuru Yoneyama, Yosuke Kurihara, Kajiro Watanabe, Hiroshi Mitoma
Gait analysis is a valuable tool for obtaining quantitative information on motor deficits in Parkinson's disease (PD). Since the characteristic gait patterns of PD patients may not be fully identified by brief examination in a clinic, long-term, and unobtrusive monitoring of their activities is essential, especially in a nonclinical setting. This paper describes a single accelerometer-based gait analysis system for the assessment of ambulatory gait properties. Acceleration data were recorded continuously for up to 24 h from normal and PD subjects, from which gait peaks were picked out and the relationship between gait cycle and vertical gait acceleration was evaluated...
November 2013: IEEE Transactions on Neural Systems and Rehabilitation Engineering
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