Apple watch detects falls, diagnoses heart rhythm, bp irregularities

The Apple Watch has become a serious medical monitor.  It will now be able to detect falls, contact emergency responders, and diagnose  irregularities in heart rhythm and blood pressure.  Its ECG app has been granted a De Novo classification by the FDA.

ECG readings are taken from the wrist, using electrodes built into the Digital Crown and an electrical heart rate sensor in the back crystal. Users touch the Digital Crown and receive a heart rhythm classification in 30 seconds. It can classify if the heart is beating in a normal pattern or whether there are signs of Atrial Fibrillation . All recordings, their associated classifications and any noted symptoms are stored and can be shared with physicians.

The watch intermittently analyzes heart rhythms in the background and sends a notification if an irregular heart rhythm such as AFib is detected.  It can also alert the user if the heart rate exceeds or falls below a specified threshold.

Fall detection is via a built in accelerometer and gyroscope, which measures forces, and an algorithm to identify hard falls. Wrist trajectory and impact acceleration are analyzed to detect falls.  Users are then sent an alert, which can be dismissed or used to call emergency services.  If  immobility  is sensed for 60 seconds,  emergency services will automatically be called, and emergency contacts will be notified.


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 JohnsonJohn MattisonRoozbeh GhaffariPoppy Crum – Phillip Alvelda Marom Bikson – Ed Simcox – Sean Lane

Gait sensor predicts senior falls

University of Illinois professors Bruce Schatz and David Buchner have developed a system to predict senior fall risk using motion sensors that measure walking patterns.

67 women over 60 were tested on walking ability,  detailed past annual falls, and wore an accelerometer for one week.

The analysis of device data and reported history enabled the researchers to accurately predict falls based on unsteadiness in standing and walking.

The goal is prevention — encouraging  those who know that they are at risk, and their physicians, to focus on strength and balance exercises.


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

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Tony Chahine on human presence, reimagined | ApplySci @ Stanford

Myant‘s Tony Chahine reimagined human presence at ApplySci’s recent Wearable Tech + Digital Health + Neurotech conference at Stanford:


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

REGISTRATION RATES INCREASE JUNE 29TH

Wall sensor monitors walking speed, stride to track health

MIT’s Dina KatabiChen-Yu Hsu, and colleagues have developed WiGait, a wall sensor that detects walking speed and stride to monitor health. This builds on previous MIT research which showed that radio signals could track breathing and heart rate, without wearables.

The  system works by transmitting low-power radio signals and analyzing how they reflect off  bodies within a radius of 9 to 12 meters. Machine learning algorithms separated walking periods from other activities and found the stable phase within each walking period.  The sensor, when combined with wearable devices, could also track Parkinson’s and MS symptoms, and help predict health events related to  heart failure,  lung disease, kidney failure, and stroke, as well as the risk of falls. Caregivers could also be notified in emergencies.


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 – Tom Insel – John Rogers – Jamshid Ghajar – Phillip Alvelda – Nathan Intrator

Sensors inform skilled nursing care

IBM has partnered with Avamere skilled nursing facilities to sudy the use of cognitive computing to improve caregiver knowledge and actions. By embedding sensors that gather physical and environmental data in  senior living facilities, Avamere hopes to reduce hospital admission rates.

Patient movement, air quality, gait analysis and other fall risk factors, personal hygiene, sleeping patterns, incontinence and trips to the bathroom will be monitored. IBM will  analyze the data to create an understanding of each patient, and be able to predict and hopefully prevent negative outcomes.

One Avemere company, Infinity Rehab, already integrates sensor – derived health data in physical, occupational, and speech therapy protocols.


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

AI assistant addresses specific needs of seniors

ElliQ is AI assistant that intuitively interacts with seniors to support independent living.

The NLP based system enables users to make video calls, play games, and use social media. Music, TED talks, audio books,and other content is recommended, after machine learning tools analyze user preferences (or caregiver input is received.)  Physical activity is suggested after a long period of sitting is detected.  Medication reminders can be scheduled.

The robot is meant to act as a companion, to address loneliness, which is an epidemic amongst the elderly.  It could be further enhanced if memory triggers, anxiety-reducing content, and custom instructions about activities of daily living were incorporated.

ApplySci’s 6th  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 – Sky Christopherson – Marcus Weldon – Krishna Shenoy – Karl Deisseroth – Shahin Farshchi – Casper de Clercq – Mary Lou Jepsen – Vivek Wadhwa – Dirk Schapeler – Miguel Nicolelis

Alexa solidifies NLP’s role in smart homes, cars. Is senior care next?

Amazon’s Alexa is the deserved  star of CES. Lights, thermostatsair purifiers, cars, refrigeratorsother appliances, and baby monitors are examples of interfaces solidifying the natural voice processing-driven future of the world.

Amazon now has the opportunity to enhance the lives of those aging in place.  Its development of senior citizen focused applications is lagging.  Alexa has the ability provide the social interaction, health monitoring, and memory triggers that many seniors need to live independently.  If caregivers were able to create customized questions and answers, specific user needs could be better addressed.

ApplySci’s 6th  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 – Sky Christopherson – Marcus Weldon – Krishna Shenoy – Karl Deisseroth – Shahin Farshchi – Casper de Clercq – Mary Lou Jepsen – Vivek Wadhwa – Dirk Schapeler – Miguel Nicolelis

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

Antibody dramatically reduces amyloid plaques in Alzheimer’s patient study

A potential game-changer in the fight against Alzheimer’s Disease has been successfully trialled. Biogen developed aducanumab was found to almost completely clear the visible signs of Alzheimer’s disease from the brain.

165 patient brains were scanned as they were given the drug. After a year, almost all of the amyloid plaques appeared to have disappeared from those given the highest doses.

The findings suggest the plaques at least partly cause the disease, and are not a byproduct.  This has long been debated.

The drug is not with out risk, however.  It caused brain swelling in some patients, who then ledt the trial.


Wearable Tech + Digital Health + NeuroTech Silicon Valley – February 7-8 @ Stanford University – Featuring:   Vinod Khosla – Tom Insel – Zhenan Bao – Phillip Alvelda – Nathan Intrator – John Rogers – Mary Lou Jepsen – Vivek Wadhwa – Miguel Nicolelis

Gait sensors predict falls, allowing preventive intervention

University of Missouri’s Marjorie Skubic has used sensors to measure gait speed and stride length, to predict falls.  The goals is to use wearables and smart home technology to preserve independence and allow seniors to age in place.

Data was collected at an independent-living style retirement residence. Images and nurse alert emails were generated when irregular motion was detected. The researchers determined that a gait speed decline of 5 centimeters per second was associated with an 86.3 percent probability of falling within three weeks.  A shortened stride length was associated with a 50.6 percent probability of falling within three weeks.


Wearable Tech + Digital Health + NeuroTech Silicon Valley – February 7-8 @ Stanford University – Featuring:   Vinod Khosla – Tom Insel – Zhenan Bao – Phillip Alvelda – Nathan Intrator – John Rogers – Mary Lou Jepsen – Vivek Wadhwa – Miguel Nicolelis