Evidence map›Paper›PMID 28303790›Full record

ArticleIET systems biology2017

Design of robust adaptive controller and feedback error learning for rehabilitation in Parkinson's disease: a simulation study.

Korosh Rouhollahi, Mehran Emadi Andani, Seyed Mahdi Karbassi, Iman Izadi

Open access · greenAbstract read
In one paragraph

Article in IET systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 20 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Korosh RouhollahiDepartment of Applied Mathematics, Yazd University, Yazd, Iran. kr_math@yahoo.com.
Mehran Emadi AndaniDepartment of Biomedical Engineering, University of Isfahan, Isfahan, Iran.
Seyed Mahdi KarbassiDepartment of Applied Mathematics, Yazd University, Yazd, Iran.
Iman IzadiDepartment of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran.
Yazd University · IRIsfahan University of Technology · IRUniversity of Isfahan · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep brain stimulation (DBS) is an efficient therapy to control movement disorders of Parkinson's tremor. Stimulation of one area of basal ganglia (BG) by DBS with no feedback is the prevalent opinion. Reduction of additional stimulatory signal delivered to the brain is the advantage of using feedback. This results in reduction of side effects caused by the excessive stimulation intensity. In fact, the stimulatory intensity of controllers is decreased proportional to reduction of hand tremor. The objective of this study is to design a new controller structure to decrease three indicators: (i) the hand tremor; (ii) the level of delivered stimulation in disease condition; and (iii) the ratio of the level of delivered stimulation in health condition to disease condition. For this purpose, the authors offer a new closed-loop control structure to stimulate two areas of BG simultaneously. One area (STN: subthalamic nucleus) is stimulated by an adaptive controller with feedback error learning. The other area (GPi: globus pallidus internal) is stimulated by a partial state feedback (PSF) controller. Considering the three indicators, the results show that, stimulating two areas simultaneously leads to better performance compared with stimulating one area only. It is shown that both PSF and adaptive controllers are robust regarding system parameter uncertainties. In addition, a method is proposed to update the parameters of the BG model in real time. As a result, the parameters of the controllers can be updated based on the new parameters of the BG model.

Indexed as

Feedback, PhysiologicalBasal GangliaBiofeedback, PsychologyDeep Brain StimulationHumansMachine LearningNeurological RehabilitationParkinson DiseaseTherapy, Computer-AssistedTreatment Outcome

Identifiers

PMID28303790
PMCPMC8687274
OpenAlexW2462749152

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.