Categories
Seniors

Device analyzes senior behavior, notifies caregivers of anomalies

Numera EverThere monitors senior health and daily activities in real time, and immediately notifies caregivers of of out-of-parameter readings.

Senior safety products are typically reactive — the most popular example being a button pushed after a wearer has fallen.  EverThere aims to be proactive, monitoring  daily activities and movement to determine anomalies which require intervention.

The service and open cloud platform  work with the Numera Libris, a 3G connected, GPS-enabled two-way voice communication device, which sends customized notifications to caregivers.

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Categories
Autism Wearables

GPS, voice monitoring wearable for special needs kids

AngelSense is a tracking and voice monitoring wearable designed for children with special needs.  Parents can:

  • Receive an automatically generated real-time schedule
  • Listen to a child’s activities
  • Receive notifications of every location change
  • Locate a lost child with a 10 second live location update
  • Automatically download photos of the day’s locations

Continuous monitoring and real time alerts are enabled by cloud-based analytics and a web app.  Subscribers receive a visual diary of the child’s day, and an interface where parents and caregivers can share information and photos.

The company’s website highlights a case study where a parent and child review photos of the child’s day:  “Every evening Josh and I watch the places he visited. By using the pictures, Josh can finally share his day with me! He understands I keep him safe and feels more confident knowing I’m with him at all times.”

AngelSense customer service is staffed  with parents of special needs kids who are  expert users of product.

While AngelSense is geared toward children, ApplySci believes that it could be also be  used as a safety solution for dementia sufferers and their caregivers.

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Categories
Robotics Seniors

Senior robots perform tasks, respond to emergencies

This picture taken on February 23, 2015 shows a polar bear robot "Robear" lifting a woman for a demonstration in Nagoya, central Japan. The "Robear", developed by Riken Institute and Sumitomo Riko, has a polar cub-like face with big doey eyes, but packs enough power to transfer frail patients from a wheelchair to a bed or a bath. A historically low birth rate and ever-increasing life expectancy means Japan's population of elderly people is growing, while the pool of youngsters to look after them is shrinking. AFP PHOTO / JIJI PRESS JAPAN OUT (Photo credit should read JIJI PRESS/AFP/Getty Images)

Robots can help seniors age in place.  Following are examples of robots that perform tasks, communicate, and notify loved ones in emergencies.

Toyota’s Human Support Robot program’s current robot prototype is compact and highly maneuverable, with a folding arm which can pick up objects off the floor, and bring things down from shelves, among other tasks.   It will be able to be operated remotely by caregivers, with the operator’s face and voice being relayed in real time.

RIKEN and Sumitomo Riko’s  nursing care robot, called Robear, can lift a person from a bed into a wheelchair, or help him/her start up. It is designed to exert force gently, including actuator units with a low gear ratio that allow for softer movement of robotic joints, and tactile, rubber sensors to lift patients.

The GiraffPlus robot works with smart home technologies  Environmental sensors provide movement data, alerting carers of falls, and physiological sensors track health metrics,  such as blood pressure.

Fraunhofer’s Care-O-bot can perform a number of fetch-and-carry tasks; entertain and communicate – reminding an elderly person of important appointments, or when to take their medication – and respond to an emergency. It is able to move towards a fallen person, while communicating  with an emergency center, which can talk to the user by video,  using the robot’s screen, speakers and microphone.

The Bristol Robotics Laboratory has developed a  a “living lab” with smart home functionality. Robotics researchers, seniors with assistive needs and those supporting them to work together to create and test home robotic solutions. The Anchor Robotics Personalized Assisted Living  facility is connected via a network of wireless sensors and Wi-fi cameras to a central controller. Data generated from the sensors will enable the researchers to detect patterns of activity in the house to build adaptable algorithms. The algorithms will then be used to record individual habits and devise personalized robotic systems adapted to individual lifestyles.

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Categories
Assistive Technologies Eyes

Drone guides visually impaired runners

University of Nevada‘s Eelke Folmer has built a  drone system that guides visually impaired runners around a track, allowing them to run without a sighted guide. A downward-facing camera follows the lines on the track. A second camera focuses on a marker on the runner’s shirt.  The quadcopter flies at eye level, 10 feet ahead of a runner, and guides with sound.  The drone adjusts its speed to accommodate the runner’s pace.

Professor Folmer’s lab is developing multiple projects aimed at improving the lives of those with limited sight.

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Categories
3-D Printing Heart

Toward a 3D printed heart

Carnegie Mellon‘s Adam Feinberg is developing 3D printing techniques that could in the future be used to repair the heart.  This work is aimed at alternative solutions for the 4,000 Americans currently waiting to receive a heart transplant.

Feinberg described his progress:  “We’ve been able to take MRI images of coronary arteries and 3-D images of embryonic hearts and 3-D bioprint them with unprecedented resolution and quality out of very soft materials like collagens, alginates and fibrins.”

The next step is to incorporate real heart cells into these 3-D printed tissue structures, providing a scaffold to help form contractile muscle.

Click to view Carnegie Mellon video.

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Categories
Computer Vision Orthopedics Seniors Sensors

Smart walker monitors gait, assesses falling probability

Footprints by Quanticare is a walker that  continuously collects passive and contextual gait data, with the goal of predicting and preventing senior falls.  Its computer vision algorithm captures spatio-temporal gait metrics of the user and sends the data to a health care provider.

The company claims that  the walker could measure an osteoarthritic limp to improve PT protocols, and that it can gauge  MS progression by measuring the difference between  steps.

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Categories
Brain

Military shockwave sensor used for sports concussion detection

Early detection of concussion can enable more rapid treatment and better outcomes.

The Linx IAS  sensor detects head impact severity during sports training.  It was built upon military technology that measures the  impact of  explosion shockwaves on the brain.

The sensor is part of fabric headband.  Concussive forces are transmitted to an app that rates each blow from 1-99.  Each rating has an associated traffic light color code.  Green signals a low level “sub-concussive” blow, while red identifies a severe hit.

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Categories
Heart

Optogenetics used to regulate heartbeat

Oxford’s Gil Bub and and Stony Brooks’ Emilia Entcheva have used optogenetics, a method used to control neurons, to regulate heartbeat.

Arrhythmia patients currently use pacemakers or drugs to control heart rhythm.   These approaches can stop or start waves, but cannot provide fine control over wave speed and direction.

In the Bub and Entcheva study, a protein called channelrhodopsin was delivered to heart cells via gene therapy.  This made them light-responsive. Using a computer-powered light projector, the researchers controlled  the speed and direction of the cardiac waves, and the orientation of spirals, in real time.  This has never before been shown in a living system.

Click to view University of Oxford video.

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Categories
Autism Brain Wearables

Glass app helps autistic kids understand expressions, emotions

Dennis Wall, Catalin Voss, and  Nick Haber of Stanford’s Wall Lab are developing Google Glass software to help autistic children recognize and understand facial expressions and emotions.

Head motion tracking sensors, a microphone, and an eye tracking infrared camera analyze a wearer’s behavior during social interactions. Real time social cues are provided, and responses, including eye contact details, which can be analyzed in behavioral therapy, are recorded. The goal is to incorporate behavioral therapy into natural settings.

Last year ApplySci described a related technology,  Brain Power‘s Glass app, where expressions are interpreted and social engagement with parents is monitored, using games and exercises.

The Autism Glass Project has been tested on 40 children, and a clinical trial of 100 participants is now beginning.

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Categories
Brain Parkinson's

Study: Cancer drug improves Parkinson’s cognitive, motor functions

A small, early stage trial (with no control group) at Georgetown has  found that a small dose of the leukemia drug nilotinib (brand name “Tasigna” by Novartis) produced “meaningful clinical improvements” in 10 out of 11 patients.

The potential impact is significant, and the researchers believe that expanded studies will validate the  promising results. During the trial, participant dopamine levels increased so much that they were advised to reduce or stop taking other drugs.

The investigators reported that one participant, who was confined to a wheelchair,  was able to walk again, and three participants who could not speak were able to hold conversations.

The study marks the first time a therapy appears to reverse the “cognitive and motor decline in patients with these neuro-degenerative disorders,” according to Professor Fernando Pagan, who led the study with Charbel Moussa.

There has been some success with stimulation treatments for Parkison’s symptoms, and advances in early diagnosis and monitoring, but there is no known cure for this debilitating disease.  (See ApplySci Parkinson’s coverage, 2013-2015.)

Click to view Georgetown University Medical Center video.

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Categories
Brain Prosthetics Sensors

Sensors allow more natural sense of touch in prosthetics

Stanford’s Zhenan Bao is developing technology that could restore a more natural sense of touch in prosthetics.  Her flexible, thin plastic sensors send signals to the brain that more closely resemble nerve messages of human skin touch sensors.

The disruptive technology has not yet been tested on humans, and researchers still need to find a safe way to pass electrical signals from prostheses to the brain for long periods.

Many teams are working toward this (see ApplySci coverage from 2013-2015).   Previous tactile sensors have however been analogue devices, where more pressure produces a stronger electrical signal, rather than a more frequent stream of pulses. The electrical signals must then be sent to another processing chip that converts the strength of the signals to a digital stream of pulses that is only then sent on to peripheral nerves or brain tissue.  Bao’s sensors send digital signals directly.

Click to view Stanford University video.

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Categories
Epilepsy Wearables

App detects seizure onset with heart rate, accelerometer data

Johns Hopkins professor Gregory Krauss has used ResearchKit to develop an app to detect the onset and duration of epileptic seizures with an Apple Watch.  Wearers must touch the watch to capture accelerometer and heart rate sensor data, and notify a caregiver.  The EpiWatch app logs seizures and responses, and tracks medication adherence and side effects.

The EpiWatch is similar in function to Embrace by Empatica, developed by MIT professor Rosalind Picard.  Embrace uses skin conductance, accelerator, and gyrometer  data to detect seizures.  (See ApplySci, November 28, 2014.)

ApplySci applauds these advances, which by recording patterns and notifying loved ones,  have the potential to improve the lives of epilepsy sufferers.  There is little evidence that cardiac activity alone can be used to predict seizures (see Amir Geva‘s paper in IEEE Transactions on Biomedical Engineering).  The next step is to develop the ability to predict seizures in advance, which will require brain activity interpretation.

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