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Journal of Neurology

, Volume 265, Issue 11, pp 2656–2665 | Cite as

Sensor-based gait analysis of individualized improvement during apomorphine titration in Parkinson’s disease

  • Franz Marxreiter
  • Heiko Gaßner
  • Olga Borozdina
  • Jens Barth
  • Zacharias Kohl
  • Johannes C. M. Schlachetzki
  • Caroline Thun-Hohenstein
  • Dieter Volc
  • Bjoern M. Eskofier
  • Jürgen Winkler
  • Jochen Klucken
Original Communication
  • 81 Downloads

Abstract

Mobile, sensor-based gait analysis in Parkinson’s disease (PD) facilitates the objective measurement of gait parameters in cross-sectional studies. Besides becoming outcome measures for clinical studies, the application of gait parameters in personalized clinical decision support is limited. Therefore, the aim of this study was to evaluate whether the individual response of PD patients to dopaminergic treatment may be measured by sensor-based gait analysis. 13 PD patients received apomorphine every 15 min to incrementally increase the bioavailable apomorphine dose. Motor performance (UPDRS III) was assessed 10 min after each apomorphine injection. Gait parameters were obtained after each UPDRS III rating from a 2 × 10 m gait sequence, providing 41.2 ± 9.2 strides per patient and injection. Gait parameters and UPDRS III ratings were compared cross-sectionally after apomorphine titration, and more importantly between consecutive injections for each patient individually. For the individual response, the effect size Cohen’s d for gait parameter changes was calculated based on the stride variations of each gait sequence after each injection. Cross-sectionally, apomorphine improved stride speed, length, gait velocity, maximum toe clearance, and toe off angle. Between injections, the effect size for individual changes in stride speed, length, and maximum toe clearance correlated to the motor improvement in each patient. In addition, significant changes of stride length between injections were significantly associated with UPDRS III improvements. We therefore show, that sensor-based gait analysis provides objective gait parameters that support clinical assessment of individual PD patients during dopaminergic treatment. We propose clinically relevant instrumented gait parameters for treatment studies and especially clinical care.

Keywords

Parkinson’s disease Sensor-based gait analysis Apomorphine Gait parameter Precision medicine 

Notes

Acknowledgements

The authors would like to thank the study nurses (Kathrin Weinmann and Susanne Seifert) for their support, and the participants in this study.

Author contributions

FM: study concept and design, acquisition of data, analysis and interpretation of data, and wrote the manuscript. HG: acquisition of data, study design, and revision of the manuscript. OB: statistical revision of the manuscript. JS: acquisition of data and revision of the manuscript. Jens Barth: analysis and interpretation of data. ZK: acquisition of data and revision of the manuscript. CT-H: acquisition of data. DV: acquisition of data. BME: analysis and interpretation of data, and revision of the manuscript. JW: acquisition of data, critical revision and editing of manuscript for intellectual content. JK: initiation of the study, acquisition of data, analysis and interpretation of data, and revision and editing of the manuscript.

Compliance with ethical standards

Conflicts of interest

This study was supported by LicherMT GmbH and an intramural grant (Emerging Field Initiative—EFI_Moves) of the Friedrich-Alexander University Erlangen-Nürnberg (FAU). This work has been supported by MoveIT, an EIT Health innovation project. EIT Health is supported by EIT, a body of the European Union. The funding sources had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. Franz Marxreiter is supported by the Interdisciplinary Center for Clinical Research (IZKF) at the University Hospital of the University of Erlangen-Nuremberg (Clinician Scientist Program; Junior project 51). He received travel grants from IPSEN and Abbvie Inc. Bjoern M Eskofier reports grants outside the submitted work from Adidas AG, Agaplesion gAG, and Bosch Sensortec GmbH. He received compensation from lecturing for AbbVie Deutschland GmbH & Co. KG and Agaplesion gAG. He is a co-founder and co-owner of Portabiles GmbH and Portabiles HealthCare Technologies GmbH, and co-inventor of gait analysis patent application EP 16174268.9. Jochen Klucken received compensation and honoraria from serving on scientific advisory boards for LicherMT GmbH, Abbvie GmbH, UCB Pharma GmbH and GlaxoSmithKline GmbH & Co. KG, Athenion GmbH, Thomashilfen GmbH and from lecturing for UCB Pharma GmbH, TEVA Pharma GmbH, Licher MT GmbH, Desitin GmbH, Abbvie GmbH, Solvay Pharmaceuticals, and Ever Neuro Pharma GmbH. He holds shares from Portabiles GmbH, Portabiles HCT GmbH, and alpha-Telemed AG and is and co-inventor of gait analysis patent application EP 16174268.9. Jürgen Winkler reports personal fees outside of the submitted work from Desitin Arzneimittel GmbH, Abbvie GmbH & Co. KG, and Biogen GmbH. The other authors declare no competing interests.

Supplementary material

415_2018_9012_MOESM1_ESM.pdf (406 kb)
Supplementary material 1 (PDF 405 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Molecular NeurologyUniversity Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU)ErlangenGermany
  2. 2.Department of Computer Science, Machine Learning and Data Analytics LabFAU Erlangen-NürnbergErlangenGermany
  3. 3.Department of NeurologyPrivatklinik ConfraternitaetViennaAustria
  4. 4.Department of Applied Econometrics and International Political EconomyGoethe University FrankfurtFrankfurtGermany

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