Robotics in PT Flashcards
HISTORY
Identify the year:
- Purpose of robotics: for military purposes
1965
HISTORY
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- Full body exoskeleton
1965
HISTORY
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- Hardiman by General Electric (US)
1965
HISTORY
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- First exoskeletons for gait assistance
- Mihajlo Pupin Institute Serbia
- University of Wisconsin-Madison, US
1970’s
HISTORY
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- RTX manipulator touch-sensitive pad as an end-effector
- Recorded response times, could be compared to previous sessions
1980
HISTORY
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- MIT-MANUS Project for rehabilitation purposes
- distinct approach to upper-extremity stroke therapy and successfully demonstrated their clinical effectiveness
1990’S
HISTORY
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- Mechanical control
- Lokomat for stroke and SCI
2001
One of the earliest devices for locomotion
Lokomat for stroke and SCI
HISTORY
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World’s first wearable cyborg
Bio-electrical signals (BES)
Birth of the Hybrid Assistive Limb (HAL)
2005
HISTORY
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Military exoskeletons (Raytheon XOS)
ReWalk, Indego (enables paraplegic patients to get out of their wheelchair)
2010
HISTORY
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Children’s Healthcare of Atlanta
First Pedia Rehab Program
Ekso Robotic Exoskeleton
Robotic devices to assist factory workers in biomechanics
2015
HISTORY
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HAL robotic exoskeleton devices were acquired by the city of Manila.
2021 & 2022
HISTORY
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Cybathlon in Switzerland
Paraplegias using robotic devices compete
2016
What were the 3 hospitals that acquired HAL robotic exoskeleton devices in 2021 and 2022?
ospital ng maynila, sta ana hospital, san andres hospital
HISTORY
Identify the year:
Filipinos made upper extremity rehabilitation robot, “AGAPAY Project” received its first international patent.
2023
- Invented in DLSU
- Exoskeleton device for UE
- Has functions for both passive and active motion
AGAPAY Project
GIVE 3 OF THE GENERAL CHARACTERISTICS OF PATIENTS WHO ARE ELIGIBLE FOR ROBOTIC REHABILITATION
-WITH MEDICAL CLEARANCE FOR AMBULATION
-GOOD CARDIOPULMONARY HEALTH
-NORMAL BONE DENSITY
-STABLE SPINE / NO UNHEALED FRACTURES
-CONTROLLED AUTONOMIC DYSREFLEXIA AND ORTHOSTATIC HYPOTENSION
-ABSENCE OF UNCONTROLLED LIMB MOVEMENTS
-NORMAL COGNITION
-WITHOUT SEVERE DEFORMITY
-MANAGEABLE SPASTICITY (MAS: GRADE 3 AND BELOW)
CORE PRINCIPLES OF EXPERIENCE-DEPENDENT NEUROPLASTICITY
- Natural networks not actively engaged in training can degrade
USE IT OR LOSE IT
CORE PRINCIPLES OF EXPERIENCE-DEPENDENT NEUROPLASTICITY
Training can induce dendritic growth and synaptogonesis within specific brain regions that enhance task performance
USE IT & IMPROVE IT
The nature of training dictates the nature of plasticity
SPECIFICITY
Repitition is required to induce lasting neural change (skill instantiation)
REPETITION MATTERS
A sufficient intensity of stimulation is required to induce plasticity
INTENSITY MATTERS
Different forms of plasticity occur at different times & during training
TIME MATTERS
The training experience must be sufficiently rewarding to induce plasticity
SALIENCE MATTERS
Training-induced plasticity occurs more readily in the younger brain
AGE MATTERS
Plasticity induced by one training experience can enhance the acquisition of similar behaviors
TRANSFERENCE
All are OMTs for the UE except:
- Action Research Arm Test
- Children’s Hand-use Experience
- Canadian Occupational Performance Measure (COPM)
- Questionnaire Quality of Upper Extremity Skills Test (QUEST)
- Modified Ashworth Scale (MAS)
Canadian Occupational Performance Measure (COPM)
Plasticity induced by one training experience can interfere the acquisition of similar behaviors
INTERFERENCE
Give 3 OMTs for the LE used in robotics for PT
- Walking ability gait speed, step length, cadence
- 6-min walking distance (6MD)
- Gross Motor Function Measure (GMFM)
- Canadian Occupational Performance Measure (COPM)
- Pediatric Evaluation of Disability Inventory
- Modified Ashworth Scale (MAS)
ELIGIBILITY
T/F
Manual Ability Classification System (MACS) Level of II-III for UE.
FALSE
Manual Ability Classification System (MACS) Level of II-IV for UE.
ELIGIBILITY
T/F
Gross Motor Function Classification System (GMFCS) levels I–IV
TRUE
ELIGIBILITY
T/F
- Able to express pain and anxiety through verbal or nonverbal communication or gestures, and facial expressions.
- Cooperative and follows instructions.
- No significant deformities or contractures.
- Sufficient limb length and size.
TRUE
The following are challenges in robotics in PT except:
- Difficulty in maintaining patient’s motivation and attention.
- Compensatory and involuntary movements such as head turning, and shoulder elevation.
- Complains of fatigue.
- Available devices specifically designed to fit younger/smaller patients. (e.g. 5 years old)
- Available devices specifically designed to fit younger/smaller patients. (e.g. 5 years old)
There is a lack of available devices specifically designed to fit younger/smaller patients. (e.g. 5 years old)
ADVANTAGES OF ROBOTICS IN PT
T/F
ENHANCE CAPACITY TO PERFORM HIGHLY REPETITIVE TASKS AND INTENSE EXERCISES
TRUE
ADVANTAGES OF ROBOTICS IN PT
T/F
LESS BURDEN TO THE PATIENT AND THE THERAPIST
TRUE
ADVANTAGES OF ROBOTICS IN PT
T/F
LESS ACCURATE ASSISTANCE, FEEDBACK AND ASSESSMENT
FALSE
MORE ACCURATE ASSISTANCE, FEEDBACK AND ASSESSMENT
ADVANTAGES OF ROBOTICS IN PT
T/F
ACCURACY AND CONSISTENCY OF MOVEMENT PATTERNS
TRUE
ADVANTAGES OF ROBOTICS IN PT
T/F
VISUALLY PLEASING
TRUE
ADVANTAGES OF ROBOTICS IN PT
T/F
Boring for the patient
FALSE.
CAPTURES THE PATIENT’S INTEREST
T/F
SOME DEVICES ARE HEAVY AND TAKES TIME AND EFFORT TO WEAR
TRUE
T/F
ROBOTICS MAY LEAD TO FRUSTRATION FROM PATIENTS WHO TAKES LONGER TO IMPROVE
TRUE
T/F
ROBOTICS IS COSTLY. IT MAY LEAD TO MISCONCEPTION THAT THE USE OF A HIGH TECH AND EXPENSIVE DEVICE WILL DEFINITELY “CURE” THEM.
TRUE
What is the goal of robotic rehabilitation?
To serve as an adjunct to conventional therapy to optimize promotion of neuroplasticity and enhance motor re-learning by providing assistance and feedback beyond the capacity of manual techniques.
- Manipulandum (handle) at the distal part of the pt will have the control which will give different controls
- Assistive, active-assistive or assist as needed or resisted motion
- Can be imbued with haptic technology (different tactile sensations introduced)
End-effector-based
Identification
Examples of End-effector-based robotics:
- Enables robotically assisted therapy exercises for the paretic fingers.
- Taped to the distal phalanges.
- Can perform passive, active assistive, and isometric activities.
- Real-time biofeedback
- Integrated EMG
AMADEO (Trymotion, Austria)
Identification
Examples of End-effector-based robotics:
-Manipulandum
-Patient can draw shapes or move their UE along a specific path.
-The kinematic data collected is useful for gauging post-stroke motor recovery.
MIT-MANUS (Interactive Motion Technologies, Cambridge, MA)
- Worn outside of the patient’s body
- Divided into stationary (fixed in an area) and mobile (portable; worn in the clinic or for personal use outside)
Exoskeleton-type
Identification
Examples of End-effector-based robotics:
-Supports motion of finger joints while detecting voluntary active motion.
-Multisensory stimulation and a simultaneous 3D animation on the screen to amplifiy the cortical stimulation.
-Patient can use his/her healthy hand to reply similar movements on the affected hand through Gloreha robotic glove.
GLOREHA SINFONIA
Identification
Examples of End-effector-based robotics:
Provides training on all stages of stroke recovery.
Has 4 different control modes:
-Passive
-Assistive
-Active
-Resistive
ARM MOTUS M2 PRO
Identification
Examples of exoskeleton type:
-Part of a unique modular therapy concept that covers the whole “Continuum of Rehabilitation”.
-Uses a single software platform throughout various devices for a specific stage of rehabilitation from early rehabilitation to long-term recovery.
ARMEO SPRING (Hocoma)
Identification
Examples of exoskeleton type:
Amplify patient’s weak bioelectrical signals.
Detects signals by using different sensors attached to the patient’s skin.
MYOMO ROBOTIC ARM (Massachusetts Institute of Technology)
Identification
Examples of exoskeleton type:
Fourier Intelligence
Amplify patient’s weak bioelectrical signals.
Detects signals by using different sensors attached to the patient’s skin.
HANDY REHAB
CONTROL STRATEGIES FOR ROBOT-ASSISTED THERAPY
EMG, ground reaction force, counterbalance
Assistance Strategies
CONTROL STRATEGIES FOR ROBOT-ASSISTED THERAPY
Resistive, constraint-induced
Challenge-based strategies
CONTROL STRATEGIES FOR ROBOT-ASSISTED THERAPY
Providing different sensations
- Proprioceptive, tactile, etc
Particularly, for UE with virtual reality
- Teaches skill to the patient
Haptic Simulation Strategies
CONTROL STRATEGIES FOR ROBOT-ASSISTED THERAPY
Type of devices that does not have contact with patients; just coaching
E.g., Assess form/posture then provide feedback and motivation
Embodied Coaching Strategies