Soft Robotic Hand for Stroke Rehabilitation

Stroke Rehabilitation

Current Methods

Existing end effectors and exoskeletons.
  • Motor Function: assess gross motor movements and a series of general impairment measures when using the upper extremities.
  • Global Stroke Severity: assess the severity of stroke through global assessment of deficits post stroke.
  • Muscle Strength: assess muscle power and strength during movement and tasks.
  • Dexterity: assess fine motor and manual skills through a variety of tasks, particularly with the use of the hand.
  • Range of Motion: assess ability to freely move upper extremity at joints both passively and actively.
  • Proprioception: assess bodily sensory awareness and location of limbs.
  • Activities of Daily Living: assess performance and level of independence in various everyday tasks.
  • Spasticity: assess the tone of muscles controlled by signals from the brain. If the part of your brain that sends these control signals is damaged by a stroke, then the muscle may become too active.

Existing Barriers With Exoskeleton Devices

Exoskeleton Hand
  • Powered lower and upper extremities exoskeletons sell for $70,000 — $120,000 each on average and can weight upwards of 51 lbs.
The ReWalk Exoskeleton

Soft Robots

Soft Robot
Soft Robots Applications

3D Printed Soft Robots

  • In fused deposition modelling (FDM) — a) and b): a thermoplastic filament is heated (ΔT) by an extrusion head and pushed through an extrusion nozzle to generate pneumatic actuators capable of lifting a 3.2kg chair.
  • Direct ink writing (DIW) — c) and d): of composite hydrogel inks using pressure.
  • Selective laser sintering (SLS) — e) and f): of thermoplastic polyurethane (TPU) powders to create a monolithic pneumatically actuated hand capable of safely interfacing with humans.
Extrusion-based and powder-based 3D printing

Drawbacks of Soft Robotics

Soft Robotic Hand for Stroke Rehabilitation

  • more degrees of freedom and a larger range of motion.
  • low component cost due to inexpensive materials (e.g. fabrics, elastomers, etc.).
  • safe human-robotic interaction due to the soft and compliant materials used for their fabrication.
  • portability.

Machine Learning

Control for Manipulation

  • Model-free controllers: usually based on machine learning techniques or empirical methods. Such controllers have great advantages in highly nonlinear, non-uniform, and unstructured environment situations where modeling is almost impossible.
  • Model-based controllers: usually need analytical models to derive the controller. These controllers have more accurate and reliable performance than model-free controllers for uniform soft manipulators in known environments. However, they usually require well-defined dynamical models for the soft robots, which may not be easy to construct based on rigid-body assumptions.
  • Hybrid controllers: combine model-free and model-based controllers, and are usually based on an analytical model to capture the main part of the system’s intrinsic properties and a data learning model to compensate dynamic uncertainties.

Control Algorithm

MDP Representation

Q learning



Closed-Loop System

Sensor Characterization

Systems Characterization

Future Work




I’m a developer & innovator who enjoys building products and researching ways we can use AI, Blockchain & robotics to solve problems in healthcare and energy!

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Ensemble Technique

Sentiment Analysis in Five Steps using AutoML

Get started with Bayesian Inference

The deepest problem with deep learning

Jupyter Notebook for Data Science Coding Exercise

Multiple Linear Regression from scratch using only numpy

Blue Book for Bulldozers Competition

Data x Decision Trees (Gini)

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Alishba Imran

Alishba Imran

I’m a developer & innovator who enjoys building products and researching ways we can use AI, Blockchain & robotics to solve problems in healthcare and energy!

More from Medium

Ukraine War: Twitter Discussions, Influencers and Bots

Most popular hashtags regarding Ukraine War

Best RL algorithm to solve the Mountain Car environment by Open AI gym

Pact Modules Explained: Kadena

Using Machine Learning for Automatic 3D Anomaly (zone) Identification