iterative learning control in health care faisal karimee-01083-231 faizan rasoolee-01083-214

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Iterative Learning Control in Health Care FAISAL KARIM EE-01083-231 FAIZAN RASOOL EE-01083-214 BIO MEDICAL INSTRUMENTATION SEC B

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Iterative Learning Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214 BIO MEDICAL INSTRUMENTATION SEC B. INTRODUCTION. What is a stroke? Stroke is usually caused A blood clot blocks a vessel in the brain. Hemorrhage, in which a vessel ruptures - PowerPoint PPT Presentation

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Page 1: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

Iterative Learning Control in Health Care

FAISAL KARIM EE-01083-231FAIZAN RASOOL EE-01083-214

BIO MEDICAL INSTRUMENTATION

SEC B

Page 2: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

INTRODUCTION

What is a stroke?

Stroke is usually caused

1. A blood clot blocks a vessel in the brain.

2. Hemorrhage, in which a vessel ruptures and leaks blood into surrounding areas.

Effects of Stroke

3. Annually, 15 million people worldwide suffer a stroke and 5 million are left permanently disabled.

4. Some of the connecting nerve cells die.

Page 3: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

Stroke

Page 4: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

Introduction cont…

1. Stroke survivors often have a complex pattern of upper limb motor impairments, resulting in a loss of functional abilities such as reaching.

2. The current prognosis for upper-limb recovery following a stroke is poor, with a review reporting that complete recovery occurs in less than 15% of patients with initial paralysis.

3. Stroke is also an age-related disease.

Page 5: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

Requirements

1. There is a pressing need to improve the effectiveness of treatments.

2. Enabling rehabilitation outside the hospital, supported by mobile technology, may lead to reduced cost, increased intensity of therapy.

Research

Research into conventional therapy and motor learningtheory provides evidence that the intensity of practice of atask and feedback are important.

Page 6: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

Robotic therapy• Although the use of robotic therapy in upper-limb rehabilitation

• Robot-aided therapy improves motor control of the proximal upper limb and may improve functional outcomes.

Functional electrical stimulation (FES)

I. We use functional electrical stimulation (FES) to improve motor Control.

II. FES makes muscles work by causing electrical impulses to travel along the nerves in much the same way as electrical impulses from the brain.

III. If stimulation is carefully controlled, a useful movement can be made.

Page 7: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

FES Cont…Clinical research with the conclusion that the therapeutic benefit of stimulation is maximized when applied coincidently with a patient’s own voluntary intention to move.

How FES Works?

when FES is given the anterior horn (AH) cell synapses may be strengthened by receiving simultaneous impulses along the motor nerves due to FES and voluntary effort.

Thereby allowing AH cells to compensate for damage to thesubject’s motor system.

This Because the patient’s own voluntary intention required.

Page 8: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

FES Model-Based Control Methods

A variety of FES model-based control methods have been employed to control movement.

The majority are intended for spinal cord injury (SCI) subjects, focused on the lower limb.

A number of FES schemes required for the lower limb.

But If we give FES to musculoskeletal system then it is Required less FES schemes.

In this case muscle selectivity is easy.

.

Page 9: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

FES Cont…

1. Fuzzy control of standing, 2. Sliding mode control of Shank movement , 3. Data-driven control of the knee joint, 4. Multichannel proportional plus integral plus derivative (PID) control of the wrist.

Above Techniques have rarely transferred to clinical practice especiallyin the case of stroke rehabilitation Strategies adopted are

• Open loop• The stimulation is triggered using limb position• Electromyography (EMG) signals

To provide a measure of participant’s intended movement.

Page 10: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

FES cont…

A principal reason for the lack use of model-based method is

Unreliable biomechanical models.

Moreover musculoskeletal system is highlysensitive to

A)Physiological conditions B)Including skin impedance,C)Temperature D)moistureE)Electrode placement F)Time-varying effects such as

spasticity and fatigue.

These problems are exacerbated in the case of stroke because hemiplegic subjects exhibit both voluntary and involuntary responses to applied stimulation.

Page 11: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

Iterative learning control (ILC)

Iterative learning control (ILC) Iterative learning control (ILC) is one model-based approach to stroke rehabilitation that has progressed to a program of clinical trials.

ILC exploits the repeating nature of the patients’ tasks to improve performance by learning from past experience. ILC is able to respond to physiologicalchanges in the system, such as fatigue due to feed back.

ILC can also closely regulate the amount of stimulation supplied, ensuring that minimum assistance is provided.

Page 12: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

ILC-BASED STROKE REHABILITATION

Relearning skills after a stroke requires a person to practice to use feedback from previous attempts to improve the next one.

The problem is that practice is limited, or impossible, due to the effects of the stroke.

When applying we should have to measure the level of stimulation during the next applied.

The control system should exactly corresponds with that of ILC so that the voluntary effort supplied by the patient shouldincrease and the level of stimulation assistance decrease.

The ultimate aim is that the patient relearns how to do themovement without any added stimulation.

Page 13: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

ILC Cont…

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Clinical Assessment of Stroke Rehabilitation• The primary measure chosen for upper limb function is the

Action Research Arm Test (ARAT) developed to monitor function related to everyday tasks and uses a hierarchical measure of grasp, grip, pinch, and gross movement.

The reaching and grasping movements are rated on quality and speed in three dimensions.

• The primary outcome measure chosen to detect changes in upper limb impairment is the Fugal-Meyer assessment (FMA). This test primarily assesses impairment in terms of loss or abnormality of movement.

• Electromyography (EMG) is also used as an outcome measure in the planar study and involves capturing the electrical activity of muscles in order to study their function.

Page 15: Iterative Learning  Control in Health Care FAISAL KARIMEE-01083-231 FAIZAN RASOOLEE-01083-214

Stimulated Arm Model

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Stimulated Arm Model• To increase potential for rehabilitation, FES is applied to both the

anterior deltoid and triceps muscles in accordance with the clinical objective of providing more assistance, a greater degree of feedback, enabling more accurate movements and ensuring more muscles are usefully activated.

• The biomechanical system comprises the human arm and exoskeleton mechanical support system shown in Figure.

• The mechanical exoskeleton employed is shown in Figure and has two springs incorporated in the mechanism to provide support to overcome gravity.

• The biomechanical system comprises the human arm and exoskeleton mechanical support system shown in Figure