Human muscle tissue can perform complex calculations

A Japanese researcher has demonstrated that human muscle tissue can perform complex calculations typically reserved for electronic computers, potentially paving the way for a future where wearable devices might use our bodies as biological processors.

In a study published March 20 in IEEE Access, engineer Yo Kobayashi from Osaka University showed that the natural properties of human soft tissue can be harnessed to process information and solve mathematical equations with surprising accuracy.

“Common reservoirs include nonlinear dynamical systems like electrical circuits or tanks of fluid,” explained Kobayashi. “There are comparatively few studies that use living organisms as reservoirs, and until now, none that use in vivo human tissue.”

The research builds on a computational approach called reservoir computing, where information is processed through a complex system that can encode intricate patterns—in this case, human muscle.

Kobayashi’s experiments involved participants bending their wrists at various angles while ultrasound images captured the resulting muscle deformations in their arms. These biomechanical responses were then used as a “biophysical reservoir” to process data and perform computations.

“An ideal reservoir possesses both complexity and memory,” Kobayashi noted. “Since the mechanical responses of soft tissue inherently demonstrate stress–strain nonlinearity and viscoelasticity, muscular tissue easily satisfies these criteria.”

When tested against standard computational methods in solving complex nonlinear equations, the human tissue model consistently outperformed traditional linear regression by an order of magnitude.

The findings represent a significant departure from conventional computing, which relies on silicon-based microprocessors. Instead, this approach taps into the inherent computational capabilities of biological systems that have evolved over millions of years.

The concept may sound like science fiction, but it’s grounded in established principles of reservoir computing, a framework that has been gaining traction in computational science for over two decades. Previous research has explored using various materials as computational reservoirs, but Kobayashi’s work marks the first successful application using living human tissue.

For the average person, the most immediate application might come in the form of enhanced wearable technology. “One potential application area of this technology is wearable devices,” said Kobayashi. “In the future, it may be possible to use our own tissue as a convenient computational resource. Since soft tissue is present throughout the body, a wearable device could delegate calculations to the tissue, enhancing performance.”

This approach could potentially lead to more energy-efficient computing for certain applications, as biological systems often operate with remarkable efficiency compared to their electronic counterparts.

The research still faces significant hurdles before commercial applications become viable. Kobayashi is now focusing on scaling up his model to handle more demanding computations and investigating other biomaterials that might serve as computational reservoirs.

If successful, this merging of biology and computing could blur the lines between human and machine in ways previously unimagined. As Kobayashi put it in his conclusion, “it may not be long before machine learning is overtaken by organic learning.”

While that future remains speculative, the study offers a fascinating glimpse into how the computational power of the human body might someday complement—rather than merely use—the digital devices we carry.