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  • Frontiers in Neurology

  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Pham, Minh H.; Elshehabi, Morad; Haertner, Linda; Heger, Tanja; +8 Authors

    IntroductionAging and age-associated disorders such as Parkinson’s disease (PD) are often associated with turning difficulties, which can lead to falls and fractures. Valid assessment of turning and turning deficits specifically in non-standardized environments may foster specific treatment and prevention of consequences.MethodsRelative orientation, obtained from 3D-accelerometer and 3D-gyroscope data of a sensor worn at the lower back, was used to develop an algorithm for turning detection and qualitative analysis in PD patients and controls in non-standardized environments. The algorithm was validated with a total of 2,304 turns ≥90° extracted from an independent dataset of 20 PD patients during medication ON- and OFF-conditions and 13 older adults. Video observation by two independent clinical observers served as gold standard.ResultsIn PD patients under medication OFF, the algorithm detected turns with a sensitivity of 0.92, a specificity of 0.89, and an accuracy of 0.92. During medication ON, values were 0.92, 0.78, and 0.83. In older adults, the algorithm reached validation values of 0.94, 0.89, and 0.92. Turning magnitude (difference, 0.06°; SEM, 0.14°) and duration (difference, 0.004 s; SEM, 0.005 s) yielded high correlation values with gold standard. Overall accuracy for direction of turning was 0.995. Intra class correlation of the clinical observers was 0.92.ConclusionThis wearable sensor- and relative orientation-based algorithm yields very high agreement with clinical observation for the detection and evaluation of ≥90° turns under non-standardized conditions in PD patients and older adults. It can be suggested for the assessment of turning in daily life.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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    Frontiers in Neurology
    2017 . Peer-reviewed
    Data sources: Frontiers
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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      Frontiers in Neurology
      2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Rudroff, Thorsten; Honce, Justin M.;
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    Frontiers in Neurology
    2017 . Peer-reviewed
    Data sources: Frontiers
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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      Frontiers in Neurology
      2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: LeVine, Steven M.;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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    Frontiers in Neurology
    2016 . Peer-reviewed
    Data sources: Frontiers
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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      Frontiers in Neurology
      2016 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Robblee, Jennifer; Katzberg, Hans;

    Identifying “where is the lesion” is particularly important in the approach to the patient with focal dysfunction where a peripheral localization is suspected. This article outlines a methodical approach to the neuromuscular patient in distinguishing focal neuropathies versus radiculopathies, both of which are common presentations to the neurology clinic. This approach begins with evaluation of the sensory examination to determine whether there are irritative or negative sensory signs in a peripheral nerve or dermatomal distribution. This is followed by evaluation of deep tendon reflexes to evaluate if differential hyporeflexia can assist in the two localizations. Finally, identification of weak muscle groups unique to a nerve or myotomal pattern in the proximal and distal extremities can most reliably assist in a precise localization. The article concludes with an application of the described method to the common scenario of distinguishing radial neuropathy versus C7 radiculopathy in the setting of a wrist drop and provides additional examples for self-evaluation and reference.

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    Frontiers in Neurology
    2016 . Peer-reviewed
    Data sources: Frontiers
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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      Frontiers in Neurology
      2016 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Seamon, Bryant A.; Harris-Love, Michael O.;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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    Frontiers in Neurology
    2016 . Peer-reviewed
    Data sources: Frontiers
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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      Frontiers in Neurology
      2016 . Peer-reviewed
      Data sources: Frontiers
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Riganello, Francesco; Macrì, Simone; Alleva, Enrico; Petrini, Carlo; +3 Authors
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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    Authors: Agoston, Denes V.;
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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    Frontiers in Neurology
    2017 . Peer-reviewed
    Data sources: Frontiers
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Frontiers in Neurology
      2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Pham, Minh H.; Elshehabi, Morad; Haertner, Linda; Del Din, Silvia; +15 Authors

    IntroductionInertial measurement units (IMUs) positioned on various body locations allow detailed gait analysis even under unconstrained conditions. From a medical perspective, the assessment of vulnerable populations is of particular relevance, especially in the daily-life environment. Gait analysis algorithms need thorough validation, as many chronic diseases show specific and even unique gait patterns. The aim of this study was therefore to validate an acceleration-based step detection algorithm for patients with Parkinson’s disease (PD) and older adults in both a lab-based and home-like environment.MethodsIn this prospective observational study, data were captured from a single 6-degrees of freedom IMU (APDM) (3DOF accelerometer and 3DOF gyroscope) worn on the lower back. Detection of heel strike (HS) and toe off (TO) on a treadmill was validated against an optoelectronic system (Vicon) (11 PD patients and 12 older adults). A second independent validation study in the home-like environment was performed against video observation (20 PD patients and 12 older adults) and included step counting during turning and non-turning, defined with a previously published algorithm.ResultsA continuous wavelet transform (cwt)-based algorithm was developed for step detection with very high agreement with the optoelectronic system. HS detection in PD patients/older adults, respectively, reached 99/99% accuracy. Similar results were obtained for TO (99/100%). In HS detection, Bland–Altman plots showed a mean difference of 0.002 s [95% confidence interval (CI) −0.09 to 0.10] between the algorithm and the optoelectronic system. The Bland–Altman plot for TO detection showed mean differences of 0.00 s (95% CI −0.12 to 0.12). In the home-like assessment, the algorithm for detection of occurrence of steps during turning reached 90% (PD patients)/90% (older adults) sensitivity, 83/88% specificity, and 88/89% accuracy. The detection of steps during non-turning phases reached 91/91% sensitivity, 90/90% specificity, and 91/91% accuracy.ConclusionThis cwt-based algorithm for step detection measured at the lower back is in high agreement with the optoelectronic system in both PD patients and older adults. This approach and algorithm thus could provide a valuable tool for future research on home-based gait analysis in these vulnerable cohorts.

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    Frontiers in Neurology
    2017 . Peer-reviewed
    Data sources: Frontiers
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      Frontiers in Neurology
      2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Sokol, Leonard L.; Shapiro, Debbie; Young, Michael J.; Wise, Adina H.; +4 Authors
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    Frontiers in Neurology
    2017 . Peer-reviewed
    Data sources: Frontiers
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      Frontiers in Neurology
      2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Siepmann, Timo; Pintér, Alexandra; Buchmann, Sylvia J.; Stibal, Leonie; +16 Authors

    BackgroundIn Parkinson’s disease (PD), alpha-synuclein accumulation in cutaneous autonomic pilomotor and sudomotor nerve fibers has been linked to autonomic nervous system disturbances even in the early stages of the disease. This study aims to assess the association between alpha-synuclein-mediated structural autonomic nerve fiber damage and function in PD, elucidate the role of neuropathy progression during the early disease stages, and test reproducibility and external validity of pilomotor function assessment using quantitative pilomotor axon-reflex test and sudomotor function via quantitative direct and indirect test of sudomotor function.Methods/designA prospective controlled study will be conducted at four study sites in Europe and the USA. Fifty-two male and female patients with idiopathic PD (Hoehn and Yahr 1–2) and 52 age- and sex-matched healthy controls will be recruited. Axon-reflex-mediated pilomotor erection will be induced by iontophoresis of phenylephrine on the dorsal forearm. Silicone impressions of the response will be obtained, scanned, and quantified for pilomotor muscle impressions by number, impression size, and area of axon-reflex spread. Axon-reflex-mediated sweating following acetylcholine iontophoresis will be quantified for number and size of droplets and axon-reflex spread. Sympathetic skin responses, autonomic and motor symptoms will be evaluated. Tests will be performed at baseline, after 2 weeks, 1, 2, and 3 years. Skin biopsies will be obtained at baseline and after 3 years and will be analyzed for nerve fiber density and alpha-synuclein accumulation.DiscussionWe anticipate that progression of autonomic nerve dysfunction assessed via pilomotor and sudomotor axon-reflex tests is related to progression of autonomic symptom severity and alpha-synuclein deposition. Potential applications of the techniques include interventional studies evaluating disease-modifying approaches and clinical assessment of autonomic dysfunction in patients with PD.Clinical trail registrationTRN NCT03043768.

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    Frontiers in Neurology
    2017 . Peer-reviewed
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      Frontiers in Neurology
      2017 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Pham, Minh H.; Elshehabi, Morad; Haertner, Linda; Heger, Tanja; +8 Authors

    IntroductionAging and age-associated disorders such as Parkinson’s disease (PD) are often associated with turning difficulties, which can lead to falls and fractures. Valid assessment of turning and turning deficits specifically in non-standardized environments may foster specific treatment and prevention of consequences.MethodsRelative orientation, obtained from 3D-accelerometer and 3D-gyroscope data of a sensor worn at the lower back, was used to develop an algorithm for turning detection and qualitative analysis in PD patients and controls in non-standardized environments. The algorithm was validated with a total of 2,304 turns ≥90° extracted from an independent dataset of 20 PD patients during medication ON- and OFF-conditions and 13 older adults. Video observation by two independent clinical observers served as gold standard.ResultsIn PD patients under medication OFF, the algorithm detected turns with a sensitivity of 0.92, a specificity of 0.89, and an accuracy of 0.92. During medication ON, values were 0.92, 0.78, and 0.83. In older adults, the algorithm reached validation values of 0.94, 0.89, and 0.92. Turning magnitude (difference, 0.06°; SEM, 0.14°) and duration (difference, 0.004 s; SEM, 0.005 s) yielded high correlation values with gold standard. Overall accuracy for direction of turning was 0.995. Intra class correlation of the clinical observers was 0.92.ConclusionThis wearable sensor- and relative orientation-based algorithm yields very high agreement with clinical observation for the detection and evaluation of ≥90° turns under non-standardized conditions in PD patients and older adults. It can be suggested for the assessment of turning in daily life.

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    Frontiers in Neurology
    2017 . Peer-reviewed
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      Frontiers in Neurology
      2017 . Peer-reviewed
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    Authors: Rudroff, Thorsten; Honce, Justin M.;
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    Frontiers in Neurology
    2017 . Peer-reviewed
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      Frontiers in Neurology
      2017 . Peer-reviewed
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    Authors: LeVine, Steven M.;
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    Frontiers in Neurology
    2016 . Peer-reviewed
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      Frontiers in Neurology
      2016 . Peer-reviewed
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    Authors: Robblee, Jennifer; Katzberg, Hans;

    Identifying “where is the lesion” is particularly important in the approach to the patient with focal dysfunction where a peripheral localization is suspected. This article outlines a methodical approach to the neuromuscular patient in distinguishing focal neuropathies versus radiculopathies, both of which are common presentations to the neurology clinic. This approach begins with evaluation of the sensory examination to determine whether there are irritative or negative sensory signs in a peripheral nerve or dermatomal distribution. This is followed by evaluation of deep tendon reflexes to evaluate if differential hyporeflexia can assist in the two localizations. Finally, identification of weak muscle groups unique to a nerve or myotomal pattern in the proximal and distal extremities can most reliably assist in a precise localization. The article concludes with an application of the described method to the common scenario of distinguishing radial neuropathy versus C7 radiculopathy in the setting of a wrist drop and provides additional examples for self-evaluation and reference.

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    Frontiers in Neurology
    2016 . Peer-reviewed
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      Frontiers in Neurology
      2016 . Peer-reviewed
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    Authors: Seamon, Bryant A.; Harris-Love, Michael O.;
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    Frontiers in Neurology
    2016 . Peer-reviewed
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      Frontiers in Neurology
      2016 . Peer-reviewed
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    Authors: Riganello, Francesco; Macrì, Simone; Alleva, Enrico; Petrini, Carlo; +3 Authors
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    Authors: Agoston, Denes V.;
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    Frontiers in Neurology
    2017 . Peer-reviewed
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      Frontiers in Neurology
      2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Pham, Minh H.; Elshehabi, Morad; Haertner, Linda; Del Din, Silvia; +15 Authors

    IntroductionInertial measurement units (IMUs) positioned on various body locations allow detailed gait analysis even under unconstrained conditions. From a medical perspective, the assessment of vulnerable populations is of particular relevance, especially in the daily-life environment. Gait analysis algorithms need thorough validation, as many chronic diseases show specific and even unique gait patterns. The aim of this study was therefore to validate an acceleration-based step detection algorithm for patients with Parkinson’s disease (PD) and older adults in both a lab-based and home-like environment.MethodsIn this prospective observational study, data were captured from a single 6-degrees of freedom IMU (APDM) (3DOF accelerometer and 3DOF gyroscope) worn on the lower back. Detection of heel strike (HS) and toe off (TO) on a treadmill was validated against an optoelectronic system (Vicon) (11 PD patients and 12 older adults). A second independent validation study in the home-like environment was performed against video observation (20 PD patients and 12 older adults) and included step counting during turning and non-turning, defined with a previously published algorithm.ResultsA continuous wavelet transform (cwt)-based algorithm was developed for step detection with very high agreement with the optoelectronic system. HS detection in PD patients/older adults, respectively, reached 99/99% accuracy. Similar results were obtained for TO (99/100%). In HS detection, Bland–Altman plots showed a mean difference of 0.002 s [95% confidence interval (CI) −0.09 to 0.10] between the algorithm and the optoelectronic system. The Bland–Altman plot for TO detection showed mean differences of 0.00 s (95% CI −0.12 to 0.12). In the home-like assessment, the algorithm for detection of occurrence of steps during turning reached 90% (PD patients)/90% (older adults) sensitivity, 83/88% specificity, and 88/89% accuracy. The detection of steps during non-turning phases reached 91/91% sensitivity, 90/90% specificity, and 91/91% accuracy.ConclusionThis cwt-based algorithm for step detection measured at the lower back is in high agreement with the optoelectronic system in both PD patients and older adults. This approach and algorithm thus could provide a valuable tool for future research on home-based gait analysis in these vulnerable cohorts.

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    Frontiers in Neurology
    2017 . Peer-reviewed
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      Frontiers in Neurology
      2017 . Peer-reviewed
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    Authors: Sokol, Leonard L.; Shapiro, Debbie; Young, Michael J.; Wise, Adina H.; +4 Authors
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    Frontiers in Neurology
    2017 . Peer-reviewed
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      Frontiers in Neurology
      2017 . Peer-reviewed
      Data sources: Frontiers
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    Authors: Siepmann, Timo; Pintér, Alexandra; Buchmann, Sylvia J.; Stibal, Leonie; +16 Authors

    BackgroundIn Parkinson’s disease (PD), alpha-synuclein accumulation in cutaneous autonomic pilomotor and sudomotor nerve fibers has been linked to autonomic nervous system disturbances even in the early stages of the disease. This study aims to assess the association between alpha-synuclein-mediated structural autonomic nerve fiber damage and function in PD, elucidate the role of neuropathy progression during the early disease stages, and test reproducibility and external validity of pilomotor function assessment using quantitative pilomotor axon-reflex test and sudomotor function via quantitative direct and indirect test of sudomotor function.Methods/designA prospective controlled study will be conducted at four study sites in Europe and the USA. Fifty-two male and female patients with idiopathic PD (Hoehn and Yahr 1–2) and 52 age- and sex-matched healthy controls will be recruited. Axon-reflex-mediated pilomotor erection will be induced by iontophoresis of phenylephrine on the dorsal forearm. Silicone impressions of the response will be obtained, scanned, and quantified for pilomotor muscle impressions by number, impression size, and area of axon-reflex spread. Axon-reflex-mediated sweating following acetylcholine iontophoresis will be quantified for number and size of droplets and axon-reflex spread. Sympathetic skin responses, autonomic and motor symptoms will be evaluated. Tests will be performed at baseline, after 2 weeks, 1, 2, and 3 years. Skin biopsies will be obtained at baseline and after 3 years and will be analyzed for nerve fiber density and alpha-synuclein accumulation.DiscussionWe anticipate that progression of autonomic nerve dysfunction assessed via pilomotor and sudomotor axon-reflex tests is related to progression of autonomic symptom severity and alpha-synuclein deposition. Potential applications of the techniques include interventional studies evaluating disease-modifying approaches and clinical assessment of autonomic dysfunction in patients with PD.Clinical trail registrationTRN NCT03043768.

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    Frontiers in Neurology
    2017 . Peer-reviewed
    Data sources: Frontiers
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Frontiers in Neurolo...arrow_drop_down
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      Frontiers in Neurology
      2017 . Peer-reviewed
      Data sources: Frontiers