Literature DB >> 31641794

[Enhancing monitoring of disease progression-remote sensoring in multiple sclerosis].

M L Weidemann1, K Trentzsch1, C Torp1, T Ziemssen2.   

Abstract

BACKGROUND: As a result of innovations in the digitalization of healthcare new technologies, such as remote sensoring are gaining in importance for the collection of real-life data in addition to the regular medical examination. This enables a closer view into the daily lives of patients with multiple sclerosis and a more detailed monitoring of disease progression.
OBJECTIVE: This article gives a summary of sensor-based measurement technologies in the field of multiple sclerosis
RESULTS: A wide variety of sensor-based measurement technologies are already available, which largely focus on gait analysis and mobility. Furthermore, there are many innovative approaches for a sensor-based collation of the multifocal symptoms of multiple sclerosis, for example technologies focus on the area of stress surveillance, the autonomic nervous system, GPS tracking and sleep monitoring. DISCUSSION: Despite the existence of many already available technologies, the aim is now to find a practical way to integrate them into the daily routine of patient monitoring, which includes standardized data collection, evaluation and interpretation. Only at this point a perspective benefit for treating physicians and patients can be achieved.

Entities:  

Keywords:  Accelerometry; Big data; Digital medicine; Gait analysis; Wearable

Year:  2019        PMID: 31641794     DOI: 10.1007/s00115-019-00817-8

Source DB:  PubMed          Journal:  Nervenarzt        ISSN: 0028-2804            Impact factor:   1.214


  19 in total

1.  Body-worn motion sensors detect balance and gait deficits in people with multiple sclerosis who have normal walking speed.

Authors:  R I Spain; R J St George; A Salarian; M Mancini; J M Wagner; F B Horak; D Bourdette
Journal:  Gait Posture       Date:  2012-01-25       Impact factor: 2.840

2.  Bilateral differences in lower-limb performance in individuals with multiple sclerosis.

Authors:  Rebecca D Larson; Kevin K McCully; Daniel J Larson; William M Pryor; Lesley J White
Journal:  J Rehabil Res Dev       Date:  2013

3.  Smartphone-Based Assessment of Gait During Straight Walking, Turning, and Walking Speed Modulation in Laboratory and Free-Living Environments.

Authors:  Patima Silsupadol; Paphawee Prupetkaew; Teerawat Kamnardsiri; Vipul Lugade
Journal:  IEEE J Biomed Health Inform       Date:  2019-07-22       Impact factor: 5.772

4.  Gait and Dynamic Balance Sensing Using Wearable Foot Sensors.

Authors:  Mohamed Irfan Mohamed Refai; Bert-Jan F van Beijnum; Jaap H Buurke; Peter H Veltink
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2018-12-24       Impact factor: 3.802

5.  The validity and reliability of the GAITRite system's measurements: A preliminary evaluation.

Authors:  A L McDonough; M Batavia; F C Chen; S Kwon; J Ziai
Journal:  Arch Phys Med Rehabil       Date:  2001-03       Impact factor: 3.966

Review 6.  [Wearables in the treatment of neurological diseases-where do we stand today?]

Authors:  Jochen Klucken; Till Gladow; Johannes G Hilgert; Marc Stamminger; Christian Weigand; Björn Eskofier
Journal:  Nervenarzt       Date:  2019-08       Impact factor: 1.214

7.  Validity and repeatability of inertial measurement units for measuring gait parameters.

Authors:  Edward P Washabaugh; Tarun Kalyanaraman; Peter G Adamczyk; Edward S Claflin; Chandramouli Krishnan
Journal:  Gait Posture       Date:  2017-04-12       Impact factor: 2.840

8.  Electrocardiographic assessments and cardiac events after fingolimod first dose - a comprehensive monitoring study.

Authors:  Volker Limmroth; Tjalf Ziemssen; Michael Lang; Stephan Richter; Bert Wagner; Judith Haas; Stephan Schmidt; Kathrin Gerbershagen; Christoph Lassek; Luisa Klotz; Olaf Hoffmann; Christian Albert; Katrin Schuh; Monika Baier-Ebert; Guillaume Wendt; Heinke Schieb; Susanne Hoyer; Ralf Dechend; Wilhelm Haverkamp
Journal:  BMC Neurol       Date:  2017-01-18       Impact factor: 2.474

9.  Diagnosing and quantifying a common deficit in multiple sclerosis: Internuclear ophthalmoplegia.

Authors:  J A Nij Bijvank; L J van Rijn; L J Balk; H S Tan; B M J Uitdehaag; A Petzold
Journal:  Neurology       Date:  2019-04-19       Impact factor: 9.910

10.  Movement measurements at home for multiple sclerosis: walking speed measured by a novel ambient measurement system.

Authors:  Victoria Mj Smith; Jonathan S Varsanik; Rachel A Walker; Andrew W Russo; Kevin R Patel; Wendy Gabel; Glenn A Phillips; Zebadiah M Kimmel; Eric C Klawiter
Journal:  Mult Scler J Exp Transl Clin       Date:  2018-01-23
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  3 in total

Review 1.  Electronic Health Interventions in the Case of Multiple Sclerosis: From Theory to Practice.

Authors:  Maria Scholz; Rocco Haase; Dirk Schriefer; Isabel Voigt; Tjalf Ziemssen
Journal:  Brain Sci       Date:  2021-02-02

Review 2.  Should We Use Clinical Tools to Identify Disease Progression?

Authors:  Hernan Inojosa; Undine Proschmann; Katja Akgün; Tjalf Ziemssen
Journal:  Front Neurol       Date:  2021-01-21       Impact factor: 4.003

3.  The Dresden Protocol for Multidimensional Walking Assessment (DMWA) in Clinical Practice.

Authors:  Katrin Trentzsch; Marie Luise Weidemann; Charlotte Torp; Hernan Inojosa; Maria Scholz; Rocco Haase; Dirk Schriefer; Katja Akgün; Tjalf Ziemssen
Journal:  Front Neurosci       Date:  2020-10-26       Impact factor: 4.677

  3 in total

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