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Introduction Motor complication management is one of the main unmet needs in Parkinson's disease patients. Areas covered Among the most promising emerging approaches for handling motor complications in Parkinson's disease, adaptive deep brain stimulation strategies operating in closed-loop have emerged as pivotal to deliver sustained, near-to-physiological inputs to dysfunctional basal ganglia-cortical circuits over time. Existing sensing systems that can provide feedback signals to close the loop include biochemical-, neurophysiological- or wearable-sensors. Biochemical sensing allows to directly monitor the pharmacokinetic and pharmacodynamic of antiparkinsonian drugs and metabolites. Neurophysiological sensing relies on neurotechnologies to sense cortical or subcortical brain activity and extract real-time correlates of symptom intensity or symptom control during DBS. A more direct representation of the symptom state, particularly the phenomenological differentiation and quantification of motor symptoms, can be realized via wearable sensor technology. Expert opinion Biochemical, neurophysiologic, and wearable-based biomarkers are promising technological tools that either individually or in combination could guide adaptive therapy for Parkinson's disease motor symptoms in the future.
Dimitri Nestor Alice Van De Ville, Farnaz Delavari
Henry Markram, Felix Schürmann, Matthias Wolf, Daniel Keller, Eilif Benjamin Muller, Werner Alfons Hilda Van Geit, Michael Reimann, Srikanth Ramaswamy, James Gonzalo King, Alexis Arnaudon, András Ecker, Jean-Denis Georges Emile Courcol, Armando Romani, Pramod Shivaji Kumbhar, Rajnish Ranjan, Giuseppe Chindemi, Fernando Joaquim Leite Pereira, Christian Andreas Rössert, Michael Emiel Gevaert, Judit Planas Carbonell, Omar Awile, James Bryden Isbister, Daniela Egas Santander, Mustafa Anil Tuncel, Sirio Bolaños Puchet, Maria Reva, Natali Barros Zulaica, Samuel Lieven D. Lapere, Christoph Pokorny, Elvis Boci, Joni Henrikki Herttuainen, Genrich Ivaska, Tanguy Pierre Louis Damart, Vishal Sood, Darshan Mandge, Thomas Brice Delemontex, Aleksandra Zuzanna Teska, Polina Litvak, Jorge Blanco Alonso, Alexander Dietz, Gianluca Ficarelli, Weina Ji