Human muscle tissue can perform complex calculations

Japanese researchers show that human muscle tissue can perform complex calculations commonly used in electronic computers, which has the potential to pave the way for future wearable devices that may use our bodies as biological processors.

In a study published in an IEEE visit on March 20, Osaka University engineer YO Kobayashi showed that information can be processed using the natural properties of human soft tissue and solved mathematical equations with surprising accuracy.

“Common reservoirs include nonlinear dynamic systems, such as circuits or fluid tanks,” Kobayashi explained. “Relatively few studies have used living organisms as reservoirs, and until now, no organisms have been used in human tissues in the body.”

The study is based on a computational method called reservoir computing in which information is processed through complex systems that can encode complex patterns, in this case human muscle.

Kobayashi’s experiment involved participants bending their wrists at various angles, while ultrasound images captured muscle deformations generated on their arms. These biomechanical responses are then applied as a “biophysical reservoir” that processes the data and performs the calculation.

“The ideal reservoir has complexity and memory,” Kobayashi notes. “Since the mechanical response of soft tissues inherently exhibits nonlinearity and viscoelasticity of stress-strains, muscle tissues can easily meet these criteria.”

When tested against standard calculation methods for solving complex nonlinear equations, human tissue models always exceed the order of magnitude of traditional linear regression.

These findings are very different from conventional computing, which relies on silicon-based microprocessors. Instead, this approach leverages the inherent computing power of biological systems that have been developed for millions of years.

The concept sounds like science fiction, but it is based on established reservoir computing principles, and the framework has gained more than two decades of appeal in the field of computational science. Previous studies have explored the use of various materials as computational libraries, but Kobayashi’s work marks the first successful application of using human tissue.

For the average person, the most direct application may appear in the form of enhanced wearable technology. “One potential application area for this technology is wearable devices,” Kobayashi said. “In the future, our own tissue may be used as a convenient computing resource. Since soft tissue exists throughout the body, wearables can delegate computing to the tissue, thereby improving performance.”

This approach may lead to more energy-efficient computing in some applications, as biological systems usually operate with significant efficiency compared to electronic systems.

Until commercial applications become feasible, the study still faces significant obstacles. Kobayashi now focuses on expanding its own models to handle more demanding calculations and investigate other biological materials that may be used as computing reservoirs.

If successful, this combination of biology and computation may blur the boundaries between humans and machines in ways previously unthinkable. As Kobayashi concludes in his conclusion: “Organic learning may soon surpass machine learning.”

Although the future remains speculative, the study has a fascinating glimpse into the complement of the human body’s computing power one day (rather than just using) the digital devices we carry.