Function electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke

Pretty much useless. Insurance won't be approving treatment of chronic stroke and certainly not using these expensive products. 

Function electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke

atie L Meadmore
1*
, Ann-Marie Hughes
2
, Chris T Freeman
1
, Zhonglun Cai
1
, Daisy Tong
1
, Jane H Burridge
2
and Eric Rogers
1

Abstract

Background:
 

Novel stroke rehabilitation techniques that employ electrical stimulation (ES) and robotic technologiesare effective in reducing upper limb impairments. ES is most effective when it is applied to support the patients
’
voluntary effort; however, current systems fail to fully exploit this connection. This study builds on previous work using advanced ES controllers, and aims to investigate the feasibility of Stimulation Assistance through IterativeLearning (SAIL), a novel upper limb stroke rehabilitation system which utilises robotic support, ES, and voluntary effort.
 

Methods:
 

 Five hemiparetic, chronic stroke participants with impaired upper limb function attended 18, 1 hourintervention sessions. Participants completed virtual reality tracking tasks whereby they moved their impaired armto follow a slowly moving sphere along a specified trajectory. To do this, the participants
’
 arm was supported by arobot. ES, mediated by advanced iterative learning control (ILC) algorithms, was applied to the triceps and anteriordeltoid muscles. Each movement was repeated 6 times and ILC adjusted the amount of stimulation applied oneach trial to improve accuracy and maximise voluntary effort. Participants completed clinical assessments (Fugl-Meyer, Action Research Arm Test) at baseline and post-intervention, as well as unassisted tracking tasks at thebeginning and end of each intervention session. Data were analysed using
 t-
tests and linear regression.
 

Results:
 

 From baseline to post-intervention, Fugl-Meyer scores improved, assisted and unassisted trackingperformance improved, and the amount of ES required to assist tracking reduced.
Conclusions:
 

The concept of minimising support from ES using ILC algorithms was demonstrated. The positiveresults are promising with respect to reducing upper limb impairments following stroke, however, a larger study isrequired to confirm this.
Keywords:
 Functional electrical stimulation, Upper limb, Stroke rehabilitation, Iterative learning control, Roboticsupport, Virtual reality

Background

Stroke is a leading cause of death and disability in theUK, and about 50% of people who survive a stroke re-quire some form of rehabilitation to reduce impairment and assist with activities of daily living [1-3]. Upper limb function is particularly important in regaining independence following stroke; impairments impact on daily living and well-being [4,5]. Research has consistently identified treatment intensity and goal oriented strategies as critical elements for successful therapeutic outcomes [6-10]. To further maxi- mise rehabilitation effects, novel therapeutic and cost-effective rehabilitation interventions need to be developed and may combine different methodological techniques. For example, the combined use of electrical stimulation (ES), robot-aided therapy and virtual reality (VR) environments has been suggested to be particularly promising with respect to upper limb rehabilitation in chronic stroke [10,11].