Bio-integrated electronic tattoo measures vital signs and muscle movement

Professor Nanshu Lu at The University of Texas is developing the next-generation of flexible/stretchable electronics, photonics and therapeutics.  Pioneered by John Rogers at the University of Illionois, flexible skin “tattoos” measure vital signs and muscle movement, transmitting data wirelessly and harvesting solar energy. Future versions may play critical roles inside the body in watching for signs of disease or damage, or treating problems automatically.

Professor Lu has designed a bio-integrated electronic tattoo. The ultrathin, ultrasoft stamp-sized patch clings to the human skin without adhesive, which would interrupt electrical connectivity.  Lu’s area of expertise — the interface of flexible electronics with biosystems — is one of three areas crucial to the future of bio-integrated electronics, the others being wireless data transmission and wireless power transmission.

Medical device data shared via ultrasound, real-time treatment enabled

Navy sonar technology is being miniaturized by University at Buffalo professor Tommaso Melodia to be applied inside the human body to treat diseases like diabetes and heart failure in real time.

A network of wireless body sensors that use ultrasounds could be used to wirelessly share information between medical devices implanted in or worn by diabetic/heart failure patients.

Previously, researchers focused on linking sensors together via electromagnetic radio frequency waves – the same type used in cellular phones, GPS and wireless devices. Radio waves can be effective, but they generate heat and require large amounts of energy to propagate through skin, muscle and tissue.  Ultrasound may be a more efficient way to share information as 65 percent of the body is composed of water.  This suggests that medical devices, such as a pacemaker and a blood oxygen level monitor, could communicate more effectively via ultrasounds compared to radio waves.

Melodia highlights the technology’s use in diabetes patients, where wireless blood glucose sensors could be connected to implantable insulin pumps. The sensors would monitor the blood and, via the pumps, control the dosage of insulin as needed in real time.

Fiber optic device for lung disease detection£115m

Researchers at the University of Edinburgh, Heriot-Watt University and the University of Bath have developed a fiber-optic device to detect potentially fatal lung conditions in intensive care patients.   Its sensors will also continuously monitor blood in critically ill adults and babies with out the need for blood sampling.

The microscopic probe will detect and monitor up to 20 signs of disease in people on breathing support.  Infections, inflammation and scarring will be picked up by the probe, which is designed to be passed into the lungs and blood vessels.

Researchers hope that the probe will also help in the diagnosis of acute urinary, gastrointestinal and reproductive tract problems.

Nerve and muscle interfaces for prosthetic control

DARPA continues to build technology with academic partners to enable amputees to control prosthetic limbs with their minds.  Examples follow:

Researchers at the Rehabilitation Institute of Chicago demonstrated a type of peripheral interface called targeted muscle re-innervation (TMR). By rewiring nerves from amputated limbs, new interfaces allow for prosthetic control with existing muscles.

Researchers at Case Western Reserve University used a flat interface nerve electrode (FINE) to demonstrate direct sensory feedback. By interfacing with residual nerves in the patient’s partial limb, some sense of touch by the fingers is restored. Other existing prosthetic limb control systems rely solely on visual feedback. Unlike visual feedback, direct sensory feedback allows patients to move a hand without keeping their eyes on it—enabling simple tasks, like searching a bag for small items, not possible with today’s prosthetics.

Sensors detect flu in feverless patients

Professor Takemi Matsui of Tokyo Metropolitan University has developed a sensor based system to determine if a person is infected with the flu.  It combines thermography to monitor facial temperature, an optical sensor to count pulse rates, and microwave radar to measure respiratory rates.

Test subjects must place the palms of their hands on a screen, and results are received in 5-10 seconds. Researchers claim that the system can detect influenza sufferers with an accuracy rate of 85 percent, and healthy subjects at a rate of 90 percent.

We hope and assume that a cleaning/sterilization system is in place, ensuring that disease is not spread through the administration of the test.

Mobile phone microphones as health sensors

The Economist’s Technology Quarterly describes how mobile phone microphones are being used as versatile sensors with myriad health applications.  Examples follow:

1. Professor Tanzeem Choudhury of Cornell has created StressSense to capture and analyze voice characteristics such as amplitude and frequency. Her team concluded that “it is feasible to implement a computationally demanding stress-classification system on off-the-shelf smartphones”.

2. BeWell’s sleep-tracking feature, also by Professor Choudhury,  determines whether the phone’s user is awake or not by analyzing usage, light and sound levels, and charging habits. Physical activity is monitored using built-in accelerometers for motion-detection. Social activity is measured by sounds that indicate that the user is talking to someone, either in person or over the phone.

3. Professor John Stankovic of the University of Virginia uses microphones to capture heartbeats. Researchers in his group use earphones modified with accelerometers and additional microphones that detect the pulse in arteries in the wearer’s ear. This makes it possible to collect physical state information, including heart rate and activity level, which is transmitted to the smartphone via the audio jack.

4. Shwetak Patel of the University of Washington uses a smartphone to measure lung function when users blow on its microphone. His team has developed the SpiroSmart app, which simulates a digital spirometer, to measure the volume of air a person can expel from his or her lungs. Spirometers help doctors better understand the health status of patients with conditions like asthma, chronic obstructive pulmonary disease and cystic fibrosis.

Cornell robots anticipate human actions

Cornell University researchers have programmed a PR-2 robot to not only carry out everyday tasks, but to anticipate human behavior and adjust its actions.

From a database of 120 3-D videos of people performing common household activities, the robot has been trained to identify human activities by tracking the movements of the body – reduced to a symbolic skeleton for easy calculation – breaking them down into sub-activities like reaching, carrying, pouring or drinking, and to associate the activities with objects.

Observing a new scene with its Microsoft Kinnect 3-D camera, the robot identifies the activities it sees, considers what uses are possible with the objects in the scene and how those uses fit with the activities; it then generates a set of possible continuations into the future – such as eating, drinking, cleaning, putting away – and finally chooses the most probable. As the action continues, it constantly updates and refines its predictions.