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Category: wearables – Page 4

A research team, led by Professor Hoon Eui Jeong from the Department of Mechanical Engineering at UNIST has introduced an innovative magnetic composite artificial muscle, showcasing an impressive ability to withstand loads comparable to those of automobiles. This material achieves a stiffness enhancement of more than 2,700 times compared to conventional systems. The study is published in Nature Communications.

Soft artificial muscles, which emulate the fluidity of human muscular motion, have emerged as vital technologies in various fields, including robotics, wearable devices, and . Their inherent flexibility allows for smoother operations; however, traditional materials typically exhibit limitations in rigidity, hindering their ability to lift substantial weights and maintain precise control due to unwanted vibrations.

To overcome these challenges, researchers have employed variable rigid materials that can transition between hard and soft states. Yet, the available range for stiffness modulation has remained constrained, along with inadequate mechanical performance.

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If you’ve ever seen yourself through a thermal imaging camera, you’ll know that your body produces lots of heat. This is in fact a waste product of our metabolism. Every square foot of the human body gives off heat equivalent to about 19 matches per hour.

Unfortunately, much of this heat simply escapes into the atmosphere. Wouldn’t it be great if we could harness it to produce energy? My research has shown this would indeed be possible. My colleagues and I are discovering ways of capturing and storing body heat for energy generation, using eco-friendly materials.

The goal is to create a device that can both generate and store energy, acting like a built-in power bank for wearable tech. This could allow devices such as smart watches, fitness trackers, or GPS trackers to run much longer, or even indefinitely, by harnessing our body heat.

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MIT researchers have developed a battery-free, subcellular-sized device made of polymer designed to measure and modulate a neuron’s electrical and metabolic activity. When the device is activated by light, it can gently wrap around the neuron cell’s axons and dendrites without damaging the cells.

Scientists want to inject thousands of these tiny wireless devices into a patient’s central nervous system and then actuate them noninvasively using light. The light would penetrate the tissue and allow precise control of the devices, and thereby restore function in cases of neuronal degradation like multiple sclerosis (MS).

The MIT researchers developed these thin-film devices from a azobenzene, a soft polymer that readily reacts to light. Thin sheets of azobenzene roll into a cylinder when exposed to light, which enables them to wrap around cells. Researchers can control the direction and diameter of the rolling by changing the intensity and polarization of the light, producing a microtube with a diameter smaller than one micrometer.

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Murata is branching out from its usual ceramic components with the launch of flexible, stretchable electronics — a Stretchable Printed Circuit (SPC) platform it says is ideally positioned for wearable and medical devices.

In recent years, in the medical field, to make more accurate diagnoses, the…

Bendy, soft, stretchy devices target the wearable and medical markets.

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Wearable devices like smartwatches and fitness trackers interact with parts of our bodies to measure and learn from internal processes, such as our heart rate or sleep stages.

Now, MIT researchers have developed that may be able to perform similar functions for inside the body.

These battery-free, subcellular-sized devices, made of a soft polymer, are designed to gently wrap around different parts of neurons, such as axons and dendrites, without damaging the cells, upon wireless actuation with light. By snugly wrapping neuronal processes, they could be used to measure or modulate a neuron’s electrical and metabolic activity at a subcellular level.

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A key challenge in the effort to link brain activity with behavior is that brain activity, measured by functional magnetic resonance imaging (fMRI), for instance, is extraordinarily complex. That complexity can make it difficult to find recurring activity patterns across different people or within individuals.

In a new study, Yale researchers were able to take fMRI data, reduce its complexity, and in doing so, uncover stable patterns of activity shared across more than 300 different people. The findings, researchers say, are a promising step forward in uncovering biomarkers for psychiatric disorders.

The study was published Sept. 24 in the journal PLOS Biology.

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