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Review

Adaptive, personalized closed-loop therapy for Parkinson’s disease: biochemical, neurophysiological, and wearable sensing systems

, , , , &
Pages 1371-1388 | Received 18 May 2021, Accepted 27 Oct 2021, Published online: 17 Nov 2021
 

ABSTRACT

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.

Article highlights

• In a physiologic state, striatal dopamine is maintained at a constant concentration level, but to date, available therapies are not able to reproduce a physiological state.

• The difference between stable and fluctuating PD patients is not due to pharmacokinetics changes but mainly to pharmacodynamics changes during the disease course.

• Levodopa biochemical sensing can predict the onset of motor fluctuations and dyskinesias.

• Biochemical sensors can show different degrees of invasiveness since they can sense levodopa and its metabolite directly from blood, subcutaneous tissue, skeletal muscles, or from sweat on the skin.

• Basal ganglia beta activity (13-30Hz), is the best characterized and most promising neurophysiological biomarker for closed-loop DBS in PD.

• Knowledge on electrophysiological brain biomarkers and their temporal dynamics is increasing and algorithmic selection and combination of multiple features is likely to increase the robustness of closed-loop DBS systems.

• During gait there is a significant decrease in STN power in the high beta range (20–30 Hz) and an increase of low frequencies across the whole gait-cycle, in addition during the double support time of the gait-cycle frequencies between 8 and 20 Hz do show selective increases in power.

• Novel neurostimulators with brain sensing capabilities have been commercially released and will facilitate translation of closed-loop DBS in clinical practice.

• Wearable sensors are the only sensing systems able to provide direct feedback on the real motor status, especially for bradykinesia, tremor and gait monitoring.

• Validated FDA and CE marked wearable sensing systems are available for Parkinson’s disease symptoms monitoring.

• Semiquantitative motor diaries can be replaced by validated objective wearable driven digital diaries

• Objective wearable measurements are sensitive to therapeutic changes and validated cutoff have been established for motor status measurements, and to optimize the therapy.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Declaration of interest

L di Biase is the scientific director and one of the shareholders of Brain Innovations Srl, a University spinoff of Campus Bio-Medico University of Rome, focused on the development of advanced technologies in the Neurology field. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or conflict with the subject matter or materials discussed in this manuscript apart from those disclosed.

Additional information

Funding

The present article received no funding support..

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