neuroreha 2023; 15(04): 194-197
DOI: 10.1055/a-2180-9134
Aus der Praxis

Präzisionsrehabilitation im Neuroreha-Alltag

Mathias Bannwart

Was ist Präzisionsneurorehabilitation und weshalb ist es seit einigen Jahren ein so häufiges Schlagwort? Welche Assessments und personalisierte Trainings sind im Klinikalltag möglich? Dieser Artikel geht diesen Fragen mit Beispielen aus dem Alltag der Neurorehabilitationsklinik Cereneo nach.

Publication History

Article published online:
05 December 2023

© 2023. Thieme. All rights reserved.

Georg Thieme Verlag
Rüdigerstraße 14, 70469 Stuttgart, Germany

  • Literatur

  • 1 Béjot Y. Neurological disorders and age: The demographic transition. J Neurol Sci 2021; 429: 118028
  • 2 Ding C. et al. Global, regional, and national burden and attributable risk factors of neurological disorders: The Global Burden of Disease study 1990–2019. Front Public Heal 2022; 10: 952161
  • 3 Viruega H, Gaviria M. After 55 years of neurorehabilitation: What is the plan?. Brain Sci 2022; 12: 982
  • 4 Luft AR. How to gain evidence in neurorehabilitation: A personal view. Biomedizinische Technik Biomed Eng 2012; 57: 427-433
  • 5 French MA. et al. Precision rehabilitation: Optimizing function, adding value to health care. Arch Phys Med Rehabil 2022; 103: 1233-1239
  • 6 Rymer WZ, Reinkensmeyer DJ. Neurorehabilitation Technology. In: David J. Reinkensmeyer, Laura Marchal-Crespo, Volker Dietz, Hrsg. Neurorehabilitation Technology. Berlin: Springer; 2022: 357-365 DOI: 10.1007/978-3-031-08995-4_17
  • 7 van der Veen R. et al. Measurement feedback system for intensive neurorehabilitation after severe acquired brain injury. J Med Syst 2022; 46: 24
  • 8 Adans-Dester C. et al. Enabling precision rehabilitation interventions using wearable sensors and machine learning to track motor recovery. npj Digit Med 2020; 3: 121
  • 9 Porciuncula F. et al. Wearable movement sensors for rehabilitation: A focused review of technological and clinical advances. PMR 2018; 10: S220-S232
  • 10 Zhao Z. et al. Multimodal sensing in stroke motor rehabilitation. Adv Sens Res 2023; 2
  • 11 Rast FM, Labruyère R. Systematic review on the application of wearable inertial sensors to quantify everyday life motor activity in people with mobility impairments. J Neuroeng Rehabilitation 2020; 17: 148
  • 12 Woelfle T. et al. Wearable sensor technologies to assess motor functions in people with multiple sclerosis: Systematic scoping review and perspective. J Méd Internet Res 2023; 25: e44428
  • 13 Neishabouri A. et al. Quantification of acceleration as activity counts in ActiGraph wearable. Sci Rep 2022; 12: 11958
  • 14 Pohl J. et al. Accuracy of gait and posture classification using movement sensors in individuals with mobility impairment after stroke. Front Physiol 2022; 13: 933987
  • 15 Pohl J. et al. Classification of functional and non-functional arm use by inertial measurement units in individuals with upper limb impairment after stroke. Front Physiol 2022; 13: 952757
  • 16 Maeda Y, Sekine M, Tamura T. Relationship between measurement site and motion artifacts in wearable reflected photoplethysmography. J Méd Syst 2011; 35: 969-976
  • 17 MacKay-Lyons M. et al. Aerobic exercise recommendations to optimize best practices in care after stroke: AEROBICS 2019 Update. Phys Ther 2019; 100: 149-156
  • 18 Peters S. et al. Step number and aerobic minute exercise prescription and progression in stroke: A roadmap. Neurorehabilit Neural Repair 2022; 36: 97-102
  • 19 Koffman LJ, Crainiceanu CM, Roemmich RT, French MA. Identifying unique subgroups of individuals with stroke using heart rate and steps to characterize physical activity. J Am Hear Assoc 2023; 12: e030577
  • 20 van Dieën JH, Pijnappels M. The role of aging and movement disorders. In: Barbieri FA, Vitorio R, eds. Locomotion and Posture in older Adults. Berlin: Springer; 2017: 237-262 DOI: 10.1007/978-3-319-48980-3_16