Remote, robotic surgery for aneurysm, stroke

Vitor Mendes Pereira at Toronto Western Hospital and Krembil Brain Institute .used a Siemens Healthineers-developed robot arm to help remove an aneurysm.  A catheter was guided to the patient’s brain from an incision made near the groin in the interventional procedure.

The CorPath GRX robotics platform is controlled by joysticks and a touchscreen. A bedside  technician interacts with the robot to exchange devices including guidewires, microcatheters, and coils.

The goal is the use of robots for remote stroke patient treatment.

Join ApplySci at the 12th Wearable Tech + Digital Health + Neurotech conference on February 11-12, 2020 at Quadrus Sand Hill Road.  Speakers include:  Zhenan Bao, Stanford – Vinod Khosla, Khosla Ventures – Mark Chevillet, Facebook – Shahin Farshchi, Lux Capital – Carla Pugh, Stanford – Nathan Intrator, Tel Aviv University | Neurosteer – Wei Gao, Caltech – Sergiu Pasca, Stanford – Rudy Tanzi, Harvard – Sheng Xu, UC San Diego – Dror Ben-Zeev, University of Washington – Mikael Eliasson, Roche

Robot helps autistic kids engage

Georgia Tech professor Ayanna Howard is using interactive robots to help autistic kids engage with others,  socially and emotionally. Her company, Zyrobotics, is commericalizing this technology.

In a study, 18 kids, between the ages of 4 and 12,  five of whom had autism, interacted with two robots which expressed 20 emotional states, including boredom, excitement, and nervousness. As children heard, saw, smelled, tasted, and touched in different scenarios, the robots showed them appropriate responses. The results were increased engagement when the robots engaged with the participants in sensory stations.

Join ApplySci at the 12th Wearable Tech + Digital Health + Neurotech Boston conference on November 14, 2019 at Harvard Medical School featuring talks by Brad Ringeisen, DARPA – Joe Wang, UCSD – Carlos Pena, FDA  – George Church, Harvard – Diane Chan, MIT – Giovanni Traverso, Harvard | Brigham & Womens – Anupam Goel, UnitedHealthcare  – Nathan Intrator, Tel Aviv University | Neurosteer – Arto Nurmikko, Brown – Constance Lehman, Harvard | MGH – Mikael Eliasson, Roche – David Rhew, Samsung

Join ApplySci at the 13th Wearable Tech + Neurotech + Digital Health Silicon Valley conference on February 11-12, 2020 at Stanford University featuring talks by Zhenan Bao, Stanford – Rudy Tanzi, Harvard – David Rhew, Samsung – Carla Pugh, Stanford – Nathan Intrator, Tel Aviv University | Neurosteer

Sensor glove identifies objects

In a Nature paper, the system accurately detected  objects, including a soda can, scissors, tennis ball, spoon, pen, and mug 76 percent of the time.

The tactile sensing sensors could be used in combination with traditional computer vision and image-based datasets to give robots a more human-like understanding of interacting with objects. The dataset also measured cooperation between regions of the hand during  interactions, which could be used to customize prosthetics.

Similar sensor-based gloves used cost thousands of dollars and typically 50 sensors. The  STAG  glove costs approximately $10 to produce.

Click to view MIT video

Join ApplySci at the 12th Wearable Tech + Digital Health + Neurotech Boston conference on November 14, 2019 at Harvard Medical School and the 13th Wearable Tech + Neurotech + Digital Health Silicon Valley conference on February 11-12, 2020 at Stanford University

Thought, gesture-controlled robots

MIT CSAIL’s Daniela Rus has developed an EEG/EMG robot control system based on brain signals and finger gestures.

Building on the team’s previous brain-controlled robot work, the new system detects, in real-time, if a person notices a robot’s error. Muscle activity measurement enables the use of hand gestures to select the correct option.

According to Rus: “This work, combining EEG and EMG feedback, enables natural human-robot interactions for a broader set of applications than we’ve been able to do before using only EEG feedback. By including muscle feedback, we can use gestures to command the robot spatially, with much more nuance and specificity.”

The researchers used  a humanoid robot from Rethink Robotics, while a human controller wore electrodes on her or his head and arm.

Human supervision  increased the choice of correct target from 70 to 97 per cent.

The goal is system that can be used for people with limited mobility or language disorders.

Click to view CSAIL video

Join ApplySci at the 9th Wearable Tech + Digital Health + Neurotech Boston conference on September 24, 2018 at the MIT Media Lab.  Speakers include:  Rudy Tanzi – Mary Lou Jepsen – George ChurchRoz PicardNathan IntratorKeith JohnsonJuan EnriquezJohn MattisonRoozbeh GhaffariPoppy Crum – Phillip Alvelda Marom Bikson


Robots visualize actions, plan, with out human instruction

Sergey Levine and UC Berkeley colleagues have developed robotic learning technology that enables robots to visualize how different behaviors will affect the world around them, with out human instruction.  This ability to plan, in various scenarios,  could improve self-driving cars and robotic home assistants.

Visual foresight allows robots to predict what their cameras will see if they perform a particular sequence of movements. The robot can then learn to perform tasks without human help  or prior knowledge of physics, its environment or what the objects are.

The deep learning technology is based on dynamic neural advection. These  models predict how pixels in an image will move from one frame to the next, based on the robot’s actions. This has enabled robotic control based on video prediction to perform increasingly complex tasks.

Click to view UC Berkeley video

Join ApplySci at Wearable Tech + Digital Health + Neurotech Silicon Valley on February 26-27, 2018 at Stanford University. Speakers include:  Vinod Khosla – Justin Sanchez – Brian Otis – Bryan Johnson – Zhenan Bao – Nathan Intrator – Carla Pugh – Jamshid Ghajar – Mark Kendall – Robert Greenberg – Darin Okuda – Jason Heikenfeld – Bob Knight – Phillip Alvelda – Paul Nuyujukian –  Peter Fischer – Tony Chahine – Shahin Farshchi – Ambar Bhattacharyya – Adam D’Augelli – Juan-Pablo Mas – Michael Eggleston – Walter Greenleaf

Robot “patients” for medical research, training

In addition to robots with increasingly human-like faces, being used as companions, “patient” robots are being developed to test medical equipment and procedures on babies and adults.

Yoshio Matsumoto  and AIST colleagues created a robotic skeletal structure of the lower half of the body, with 22 moveable joints.  Its skeleton is made of metal, and its skin, fat and muscles of silicone. Embedded sensors measure pressure on various parts of the lower body. It is being used to develop hospital beds with a reduced risk of pressure wounds.

Waseda University’s Hiroyuki Ishii has developed a robot baby for practicing  breathing protocols after birth. If non-breathing babies do not respond to sensory stimulation, a tube is inserted into the trachea.  This happens in  1-2% of newborns, and poses obvious risks. The robot is designed to train medical staff to properly insert the tube into the baby’s windpipe.

The use  of robots as personal assistants, and to test procedures, will increase rapidly as advanced sensors are built into the devices.

Join ApplySci at Wearable Tech + Digital Health + Neurotech Silicon Valley on February 26-27, 2018 at Stanford University, featuring:  Vinod KhoslaJustin SanchezBrian OtisBryan JohnsonZhenan BaoNathan IntratorCarla PughJamshid Ghajar – Mark Kendall – Robert Greenberg Darin Okuda Jason Heikenfeld

Deep learning driven prosthetic hand + camera recognize, automate required grips

Ghazal Ghazai and Newcastle University colleagues have developed a deep learning driven prosthetic hand + camera system that allow wearers to reach for objects automatically.  Current prosthetic hands are controlled  via a user’s myoelectric signals, requiring learning, practice, concentration and time.

A convolutional neural network was trained it with images of  500 graspable objects, and taught  to recognize the grip needed for each. Objects were grouped by size, shape, and orientation, and the hand was programmed to perform four different grasps to accommodate them: palm wrist neutral (to pick up a cup); palm wrist pronated (to pick up the TV remote); tripod (thumb and two fingers), and pinch (thumb and first finger).

The hand’s camera takes a picture of the object in front of it, assesses its shape and size, picks the most appropriate grasp, and triggers a series of hand movements, within milliseconds.

In a small study of the technology, subjects successfully picked up and moved objects with an 88 per cent success rate.

The work is part of an effort to develop a bionic hand that senses pressure and temperature, and transmits the information to the brain.

Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston on September 19, 2017 at the MIT Media Lab. Featuring Joi Ito – Ed Boyden – Roz Picard – George Church – Nathan Intrator –  Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda

Solar powered, highly sensitive, graphene “skin” for robots, prosthetics

Professor Ravinder Dahiya, at the University of Glasgow, has created a robotic hand with solar-powered graphene “skin” that he claims is more sensitive than a human hand.  The flexible, tactile, energy autonomous “skin” could be used in health monitoring wearables and in prosthetics, reducing the need for external chargers. (Dahiya is now developing a low-cost 3-D printed prosthetic hand incorporating the skin.)

Click to view University of Glasgow video

Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston – Featuring Roz Picard, Tom Insel, John Rogers, Jamshid Ghajar and  Nathan Intrator – September 19, 2017 at the MIT Media Lab


Robots support neural and physical rehab in stroke, cerebral palsy

Georgia Tech’s  Ayanna Howard has developed Darwin, a socially interactive robot that encourages children to play an active role in physical therapy.

Specific targeting children with cerebral palsy (who are involved in current studies),  autism, or tbi, the robot is designed to function in the home, to supplement services provided by  clinicians.  It engages users as their human therapist would — monitoring performance, and providing motivation and feedback.In a recent experiment, motion trackers monitored user movements as Darwin offered encouragement, and demonstrated movements when they were not performed correctly.  Researchers claimed that wth the exception of one case, the robot’s impact was “significantly positive.

Darwin is still evolving (pun intended) and has not yet been commercialized.

At MIT,  Newman Lab researcher Hermano Igo Krebs has been using robots for gait and balance neurorehabilitation in stroke and cerebral palsy patients since 1989.  Krebs’s technology continues to be incorporated into  Burke Rehabilitation hospital treatment plans.

Join ApplySci at Wearable Tech + Digital Health + NeuroTech Boston – Featuring Roz Picard, Tom Insel, John Rogers and Nathan Intrator – September 19, 2017 at the MIT Media Lab

Sensors + robotics + AI for safer aging in place

IBM and rice University are developing MERA — a Waston enabled robot meant to help seniors age in place.

The system comprises a Pepper robot  interface, Watson, and Rice’s CameraVitals project, which calculates vital signs by recording video of a person’s face.  Vitals are measured multiple times each day. Caregivers are informed if the the camera and/or accelerometer detect a fall.

Speech to Text, Text to Speech and Natural Language Classifier APIs are being studied to enable answers to health related questions, such as “What are the symptoms of anxiety?” or “What is my heart rate?”

The company  believes that sensors plus cognitive computing can give clinicians and caregivers insights to enable better care decisions. They will soon test the technology in partnership with Sole Cooperativa, to monitor the daily activities of seniors in Italy.

Click to view IBM video

ApplySci’s 6th   Wearable Tech + Digital Health + NeuroTech Silicon Valley  –  February 7-8 2017 @ Stanford   |   Featuring:   Vinod Khosla – Tom Insel – Zhenan Bao – Phillip Alvelda – Nathan Intrator – John Rogers – Roozbeh Ghaffari –Tarun Wadhwa – Eythor Bender – Unity Stoakes – Mounir Zok – Krishna Shenoy – Karl Deisseroth – Shahin Farshchi – Casper de Clercq – Mary Lou Jepsen – Vivek Wadhwa – Dirk Schapeler – Miguel Nicolelis