1,295 research outputs found

    Inertial Sensing to Determine Movement Disorder Motion Present before and after Treatment

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    There has been a lot of interest in recent years in using inertial sensors (accelerometers and gyroscopes) to monitor movement disorder motion and monitor the efficacy of treatment options. Two of the most prominent movement disorders, which are under evaluation in this research paper, are essential tremor (ET) and Parkinson’s disease (PD). These movement disorders are first evaluated to show that ET and PD motion often depict more (tremor) motion content in the 3–12 Hz frequency band of interest than control data and that such tremor motion can be characterized using inertial sensors. As well, coherence analysis is used to compare between pairs of many of the six degrees-of-freedom of motions under evaluation, to determine the similarity in tremor motion for the various degrees-of-freedom at different frequency bands of interest. It was quite surprising that this coherence analysis depicts that there is a statistically significant relationship using coherence analysis when differentiating between control and effectively medicated PD motion. The statistical analysis uncovers the novel finding that PD medication induced dyskinesia is depicted within coherence data from inertial signals. Dyskinesia is involuntary motion or the absence of intended motion, and it is a common side effect among medicated PD patients. The results show that inertial sensors can be used to differentiate between effectively medicated PD motion and control motion; such a differentiation can often be difficult to perform with the human eye because effectively medicated PD patients tend to not produce much tremor. As well, the finding that PD motion, when well medicated, does still differ significantly from control motion allows for researchers to quantify potential deficiencies in the use of medication. By using inertial sensors to spot such deficiencies, as outlined in this research paper, it is hoped that medications with even a larger degree of efficacy can be created in the future

    Sense of agency disturbances in movement disorders: A comprehensive review

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    Sense of agency refers to the experience that one’s self-generated action causes an event in the external environment. Here, we review the behavioural and brain evidence of aberrant experiences of agency in movement disorders, clinical conditions characterized by either a paucity or an excess of movements unrelated to the patient’s intention. We show that specific abnormal agency experiences characterize several movement disorders. Those manifestations are typically associated with structural and functional brain abnormalities. However, the evidence is sometimes conflicting, especially when considering results obtained through different agency measures. The present review aims to create order in the existing literature on sense of agency investigations in movement disorders and to provide a coherent overview framed within current neurocognitive models of motor awareness

    Studies of physiological tremor in normal subjects and psychiatric patients

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    Empowering patients in self-management of parkinson's disease through cooperative ICT systems

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    The objective of this chapter is to demonstrate the technical feasibility and medical effectiveness of personalised services and care programmes for Parkinson's disease, based on the combination of mHealth applications, cooperative ICTs, cloud technologies and wearable integrated devices, which empower patients to manage their health and disease in cooperation with their formal and informal caregivers, and with professional medical staff across different care settings, such as hospital and home. The presented service revolves around the use of two wearable inertial sensors, i.e. SensFoot and SensHand, for measuring foot and hand performance in the MDS-UPDRS III motor exercises. The devices were tested in medical settings with eight patients, eight hyposmic subjects and eight healthy controls, and the results demonstrated that this approach allows quantitative metrics for objective evaluation to be measured, in order to identify pre-motor/pre-clinical diagnosis and to provide a complete service of tele-health with remote control provided by cloud technologies. © 2016, IGI Global. All rights reserved

    Exploration of digital biomarkers in chronic low back pain and Parkinson’s disease

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    Chronic pain and Parkinson’s disease are illnesses with personal disease progression, symptoms, and the experience of these. The ability to measure and monitor the symptoms by digitally and remotely is still limited. The aim was to study the usability and feasibility of real-world data from wearables, mobile devices, and patients in exploring digital biomarkers in these diseases. The key hypothesis was that this allows us to measure, analyse and detect clinically valid digital signals in movement, heart rate and skin conductance data. The laboratory grade data in chronic pain were collected in an open feasibility study by using a program and built-in sensors in virtual reality devices. The real-world data were collected with a randomized clinical study by clinical assessments, built-in sensors, and two wearables. The laboratory grade dataset in Parkinson’s disease was obtained from Michael J. Fox Foundation. It contained sensor data from three wearables with clinical assessments. The real-world data were collected with a clinical study by clinical assessments, a wearable, and a mobile application. With both diseases the laboratory grade data were first explored, before the real-world data were analyzed. The classification of chronic pain patients with the laboratory grade movement data was possible with a high accuracy. A novel real-world digital signal that correlates with clinical outcomes was found in chronic low back pain patients. A model that was able to detect different movement states was developed with laboratory grade Parkinson’s disease data. A detection of these states followed by the quantification of symptoms was found to be a potential method for the future. The usability of data collection methods in both diseases were found promising. In the future the analyses of movement data in these diseases could be further researched and validated as a movement based digital biomarkers to be used as a surrogate or additional endpoint. Combining the data science with the optimal usability enables the exploitation of digital biomarkers in clinical trials and treatment.Digitaalisten biomarkkereiden tunnistaminen kroonisessĂ€ alaselkĂ€kivussa ja Parkinsonin taudissa Krooninen kipu ja Parkinsonin tauti ovat oireiden, oirekokemuksen sekĂ€ taudin kehittymisen osalta yksilöllisiĂ€ sairauksia. Kyky mitata ja seurata oireita etĂ€nĂ€ on vielĂ€ alkeellista. VĂ€itöskirjassa tutkittiin kaupallisten mobiili- ja Ă€lylaitteiden hyödyntĂ€mistĂ€ digitaalisten biomarkkereiden löytĂ€misessĂ€ nĂ€issĂ€ taudeissa. PÀÀolettamus oli, ettĂ€ kaupallisten Ă€lylaitteiden avulla kyetÀÀn tunnistamaan kliinisesti hyödyllisiĂ€ digitaalisia signaaleja. Kroonisen kivun laboratorio-tasoinen data kerĂ€ttiin tĂ€tĂ€ varten kehitettyĂ€ ohjelmistoa sekĂ€ kaupallisia antureita kĂ€yttĂ€en. Reaaliaikainen kipudata kerĂ€ttiin erillisen hoito-ohjelmiston tehoa ja turvallisuutta mitanneessa kliinisessĂ€ tutkimuksessa sekĂ€ kliinisiĂ€ arviointeja ettĂ€ anturidataa hyödyntĂ€en. Laboratorio-tasoinena datana Parkinsonin taudissa kĂ€ytettiin Michael J. Fox Foundationin kolmella eri Ă€lylaitteella ja kliinisin arvioinnein kerĂ€ttyĂ€ dataa. Reaaliaikainen data kerĂ€ttiin kĂ€yttĂ€en kliinisia arviointeja, Ă€lyranneketta ja mobiilisovellusta. Molempien indikaatioiden kohdalla laboratoriodatalle tehtyĂ€ eksploratiivista analyysia hyödynnettiin itse reaaliaikaisen datan analysoinnissa. Kipupotilaiden tunnistaminen laboratorio-tasoisesta liikedatasta oli mahdollista korkealla tarkkuudella. Reaaliaikaisesta liikedatasta löytyi uusi kliinisten arviointien kanssa korreloiva digitaalinen signaali. Parkinsonin taudin datasta kehitettiin uusi liiketyyppien tunnistamiseen tarkoitettu koneoppimis-malli. Sen hyödyntĂ€minen liikedatan liiketyyppien tunnistamisessa ennen varsinaista oireiden mittausta on lupaava menetelmĂ€. KĂ€ytettĂ€vyys molempien tautien reaaliaikaisissa mittausmenetelmissĂ€ havaittiin toimivaksi. Reaaliaikaiseen, kaupallisin laittein kerĂ€ttĂ€vÀÀn liikedataan pohjautuvat digitaaliset biomarkkerit ovat lupaava kohde jatkotutkimukselle. Uusien analyysimenetelmien yhdistĂ€minen optimaaliseen kĂ€ytettĂ€vyyteen mahdollistaa tulevaisuudessa digitaalisten biomarkkereiden hyödyntĂ€misen sekĂ€ kroonisten tautien kliinisessĂ€ tutkimuksessa ettĂ€ itse hoidossa

    Functional motor disorders: mechanism, prognosis and treatment

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    Functional motor disorders (FMD) consist of tremor, jerky movements, altered posturing or weakness. They are characterized by specific factors in the history and neurological examination, pointing at their functional nature, like the influence of attention and distraction or incongruency with the anatomy. They are highly prevalent and often significantly impairing. This thesis discusses the pathophysiology, prognosis and treatment of FMD. Part 1 describes that we found many similarities between groups of different functional motor symptoms. Many patients report severe fatigue, which correlates with impaired quality of life and subjective health ratings. This calls for more attention in clinical practice. A comparison between cortical myoclonus and functional jerky movements showed comparable percentages of depressive and anxiety symptoms. Pain is more prevalent in functional jerky movements. Two chapters investigating fMRI in FMS, confirm existing theories on the role of altered attentional processes, perception of body scheme and sense of agency. Part 2 contains a review and a case-control study on the prognosis of FMS. It turns out symptoms did not resolve in a large part of the studied patients and misdiagnosis was low. Part 3 summarized the literature on the treatment on FMD and contains a RCT to the effect of education and self-help on the internet compared to usual care. We did not find differences between groups on clinically relevant outcome measures. Patients did report high satisfaction with the intervention

    Neuroimaging of fetal cell therapy in Parkinson’s disease

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    Parkinson’s disease is the second most common neurodegenerative disease characterised by the elevated formation of α-synuclein-immunopositive intraneuronal proteinaceous inclusions (Lewy pathology) and the progressive loss of neuromelanin-laden dopaminergic cells of the substantia nigra pars compacta, resulting in the loss of striatal dopaminergic terminals and emergence of cardinal motor features including bradykinesia, rigidity, tremor and postural instability. Dopaminomimetic agents provide effective symptomatic relief in the early stages of illness, yet due to the inherently progressive nature of the disease and the induction of debilitating side effects their efficacy is eventually lost. Cellular restorative strategies involving intrastriatal transplantation of human fetal ventral mesencephalic (hfVM) tissue gained traction from the early 1990’s, when several multi-disciplinary teams reported drastic motoric improvements concomitant with graft-derived dopaminergic re-innervation. However, outcomes of double-blind randomised controlled trials and the presentation of novel dyskinetic movements persisting in the “off-state” called for substantial revision of cell delivery strategies. The current thesis utilises positron emission tomography to examine the effects of hfVM implantation under the Transeuro protocol on dopaminergic ([18F]FDOPA, [11C]PE2I) and serotonergic ([11C]DASB) systems in patients with Parkinson’s disease and elucidate the neural underpinnings of its clinical impact. The main findings are; 1) implanted hfVM tissue led to increases in putamenal dopamine synthesis and storage capacity, dopamine and serotonin transporter density as compared to non-transplanted patients; 2) modification to surgical procedures provided inhomogenous and inconsistent re-innervation; 3) hfVM transplantation was associated with clinical improvements in measures of bradykinesia, rigidity and tremor; 4) graft-related changes in posterior putamenal dopamine and serotonin transporter density predicted symptomatic relief of bradykinesia and tremor; 5) heterogeneity of posterior putamenal re-innervation may impact upon potential clinical benefit; 6) graft-induced dyskinesia was associated with greater post-operative increases in dopamine transporter expression in the anterior putamen; 7) there was no evidence that graft-induced dyskinesia was related to serotonergic hyperinnervation. The novel findings presented in this thesis have major implications for cell-based restorative strategies beyond the hfVM era and will likely foster informed [re]consideration of many aspects of therapeutic delivery and trial design. For its ability to provide mechanistic insight in vivo, neuroimaging may continue to play a central role in the optimisation of future interventions.Open Acces
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