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The Future of Touch: How Neural Networks are Revolutionizing Prosthetics

November 27, 2025

You might be familiar with The Amazing Spiderman where Dr. Connors, the villain, has an amputated arm. He tests reptilian DNA to see how to regenerate tissue. Instead of simply regrowing his arm, he becomes the Lizard and terrorizes New York City. This story was focused on the dangers and corruption of greed, but also reflects a human desire and reveals a sympathetic side: to restore something that was lost. 

Nowadays, scientists are following the same dream that Dr. Connors was pursuing, minus the whole turning into a villain issue. People are developing something even more incredible: bionic limbs that can think, feel, and move just like a biological limb can. Welcome to the world of neuroprosthetics, where the line between humans and machines is slowly merging. 

What are Prosthetics and Why Do they Matter?

Prosthetics are appliances designed to replace missing body structures for those who were born without or have gone through a traumatic experience. In history, prosthetics used to be purely mechanical and used available resources like wooden legs, hook hands, and other contraptions that are able to grab and hold objects. While these prosthetics had some functionality to it, they had many issues from skin irritation to pressure discomfort. Imagine trying to pick up an egg and you can’t feel how hard you are squeezing it. That is the feeling for millions of people suffering with this disability. 

Now, the field is evolving rapidly. There has been new prosthetic research completely restoring the human experience of touch, movement, and sensation . Researchers and scientists are asking more questions to further the impact of this field like: Can we create limbs that directly interact with the brain? Can prosthetics perceive temperature, texture, and pressure?

The answer is, increasingly, yes.

Training Machines to Speak like the Brain

The most exciting aspect of this new generation of prosthetics are neural networks. This includes our brains and AI systems that are still learning how to process similar thoughts and actions. At the core of the revolution are BCIs or brain-computer interfaces establishing a connection between neural signals and prosthetic devices.  

How it works begins with our hands. Once we conduct a hand movement, our brain sends electrical impulses to our muscles and these nerves will always release to the according limb even if it is amputated. Today, scientists are developing brain-computer interface systems that can detect and interpret nerve impulses immediately (Willsey et al., 2025). With these methods, scientists were able to find that prosthetics were responsive and even reached 97-98% accuracy in individual finger and wrist motions using artificial intelligence agents (Diu et al., 2022). These results reveal a major step towards restoring the limb as an extension of the body through AI systems and actively work as a biological device again for the patient. 

At Stanford’s Neural Prosthetics Translational Lab, scientists try to take their research to the next level where they attempt to translate neural activity to speech on the screen in front of them (NPTL, 2025). This kind of technology uses machine learning and advanced computational methods to learn the specific patient’s neural patterns and then creates a personal movement dictionary connecting the brain activity to the patient’s speech and movement.  

Making Prosthetics Feel

Going back to our Spiderman reference, Dr. Curt Connors was able to feel with his one hand. He could sense temperature, feel textures, and experience pressure, all of which he missed out on with his amputated limb. Early prosthetics lacked this sensory dimension, but now, the movement is changing that. 

Prosthetics today directly connect with brains to provide live sensory data. Studies show that they are able to recreate the nuanced feeling of hands through electrical stimulation (Greenspon et al., 2024). Researchers conduct these experiments by placing electrodes in certain parts of the brain in order to trigger the response for sensation and tactile feedback in the respective limbs. This is revolutionary for patients as it proves to reduce phantom limb pain for patients, where they still feel pain sensation despite the loss of a limb. The future of neuroprosthetics aims to make artificial touch as immersive and intuitive as possible and now scientists are on the path to finding a way. 

Osseointegration

Perhaps the most impressive breakthrough in this field is figuring out how to implement this into the body for it to coexist with the patient comfortably. Conventional prosthetics often cause discomfort, limited control and even skin irritation. Osseointegration is the integration of titanium implants into the skeletal tissue, a method to attach artificial limbs without discomfort and allows for machine learning control through embedded electrodes and sensors (Ortiz-Catalán et al., 2023). This innovation is crucial for pushing towards products that are more viable for daily use among patients. 

In a critical clinical trial, researchers experimented on a patient with a traumatic injury to her right hand. Surgeons implemented a prosthesis which then attached the bionic hand to her forearm bones by placing the titanium implants directly on there. The result proved successful allowing the patient to control all five phantom fingers at a completion rate of 95% in the post motion test given (Ortiz-Catalán et al., 2023). Additionally, her sensations prompted consistent neural responses revealing exceptional sensory feedback. This surgery proved to be very helpful as it substantially reduced patient pain as phantom limb pain decreased as well as discomfort from the prosthetics. This allowed the patient to use the prosthesis for over three years improving her overall quality of life and independence. 

Conclusions

Scientists from so many varied fields are merging to accomplish something incredible in the field of neuroprosthetics, going above and beyond biological capabilities. The goal is to design something that doesn’t wear out, use sensors and processors, and beautifully blend human and computer communication. 

This has shown how possibilities are endless and can immensely improve the lives of those struggling without body parts. Dr. Connors was wrong to turn the whole city into lizards, but his pain and suffering can be empathized with across the world. Advanced technology today is able to help amputees and paraplegics communicate with others, move again, and reestablish their neural networks. 

In the future, prosthetics may even become so progressive that its biological counterparts will be indistinguishable. Machines will be controlled by our thoughts and actions in the split of a second and move so effortlessly that people will forget they are even wearing a prosthetic. Restoring something so significant in our daily lives is truly life-changing for these individuals and merging it with technology can help us achieve that goal faster and make movement more accessible everywhere. 

 

References

Diu, K., Luu, Nguyen, A., Jiang, M., Drealan, M., Xu, J., Wu, T., Tam, W.-K., Zhao, W., Lim, B., Overstreet, C., Zhao, Q., Cheng, J., Keefer, E., & Yang, Z. (3 C.E.). Artificial Intelligence Enables Real-Time and Intuitive Control of Prostheses via Nerve Interface.

Greenspon, C. M., Valle, G., Shelchkova, N. D., Hobbs, T. G., Ceci Verbaarschot, Callier, T., Berger-Wolf, E. I., Okorokova, E. V., Hutchison, B. C., Efe Dogruoz, Sobinov, A. R., Jordan, P. M., Weiss, J. M., Fitzgerald, E. E., Prasad, D., Driesche, A. V., He, Q., Liu, F., Kirsch, R. F., & Miller, J. P. (2024). Evoking stable and precise tactile sensations via multi-electrode intracortical microstimulation of the somatosensory cortex. Nature Biomedical Engineering. https://doi.org/10.1038/s41551-024-01299-z

NPTL. (2025). NPTL; Stanford University. https://nptl.stanford.edu/

Ortiz-Catalán, M., Zbinden, J., Millenaar, J., D’Accolti, D., Controzzi, M., Clemente, F., Cappello, L., Earley, E. J., Enzo Mastinu, Justyna Kolankowska, Munoz-Novoa, M., Stewe Jönsson, Njel, C., Paolo Sassu, & Rickard Brånemark. (2023). A highly integrated bionic hand with neural control and feedback for use in daily life. Science Robotics, 8(83). https://doi.org/10.1126/scirobotics.adf7360

Willsey, M. S., Shah, N. P., Avansino, D. T., Hahn, N. V., Jamiolkowski, R. M., Kamdar, F. B., Hochberg, L. R., Willett, F. R., & Henderson, J. M. (2025). A high-performance brain–computer interface for finger decoding and quadcopter game control in an individual with paralysis. Nature Medicine. https://doi.org/10.1038/s41591-024-03341-8

 

 

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  Timothy Durham was convicted of rape when a test showed his DNA genotype matched the DNA recovered from the crime scene. Eye witnesses testified that Durham was in a different state at the time of the incident, but he wasn’t exonerated from his 3000 year sentence until follow up DNA analysis showed that the preliminary forensic analysis used in the trial was misinterpreted (Thomas et al.). DNA testing serves an invaluable part in our criminal justice system, but it comes with complications and bias that can lead to wrongful convictions and misinformed juries.  

Background:

Forensic genetics aims to identify the origin of a biological sample. It can be traced back to Karl Landsteiner who discovered human ABO blood groups. With blood groups, suspects could be eliminated based on their blood type. For example, if a suspect had type A blood and there was type B blood left at the scene by the perpetrator, the investigators could rule out the suspect. Unfortunately, the reverse didn’t work. If the suspect and perpetrator both had the same blood type, it can’t be concluded that the suspect was guilty. Blood identifiers evolved into 8 distinct categories which improved the ability to eliminate suspects, but could only conclude that (if the system matched) it might be the perpetrator or this person might be related to the perpetrator (Jobling and Gill). The field evolved in the 1980s with the discovery of Minisatellites, lines of repetitive DNA that don’t encode proteins. Minisatellite patterns in DNA create what we know today as the DNA fingerprint, and it has a much higher accuracy rate than previous methods (Augustyn et al.). Around the same time, a breakthrough for victims of sexual assault was discovered. In the case of assault, bodily fluids of both the victim and the assaulter can get mixed. A process called differential lysis was created which could selectively increase the concentration of sperm in a fluid sample thereby allowing for accurate DNA testing (Jobling and Gill). Forensics evolved to use single-locus probe testing after several years because of its ease of interpretation. It looked at specific minisatellites that had high variability between subjects. This was the first DNA-based method to be used in a criminal investigation. Two murder homicides from several years apart were connected using DNA evidence. The evidence was then used to exonerate an innocent man, and the guilty party was found when he tried to evade mandatory DNA testing for all men in the small town. His guilt was then reinforced when the DNA profiles matched, and he gave a confession (Jobling and Gill). Finding DNA at a crime scene doesn’t guarantee that you’ll find a murderer. There are issues with non-pure samples and limited samples that make DNA work difficult, and accreditation of facilities and new techniques and take time (Jobling and Gill).  

Subjectivity of DNA Interpretation:

In a 2009 publication, the National Academy of Science discusses the possibility for subjective influence in lab based forensics. The interpretation bias happens in complex cases where, for example, there could be a mixture of DNA. A study published in 2011 looked specifically at this issue. A gang rape happened in Georgia, and the mixture in DNA from the case was used to prosecute one suspect after another suspect took a plea bargain to testify against him. With DNA mixtures, there are three possible conclusions: suspect excluded, suspect cannot be excluded, and inconclusive. If the suspect is excluded, it means that there’s little to no possibility that his DNA is part of the sample. If the suspect cannot be excluded, it means that there’s a possibility that his DNA is part of the sample. In the trial, the DNA examiners who knew the context of the case concluded that the suspect being prosecuted could not be excluded. The 2011 study gave the DNA evidence from this case and the DNA profiles of the suspects to 17 forensic examiners. These examiners had no context of the case, and they all worked independently. Of the 17, only 1 came to the same conclusion (suspect cannot be excluded) as the examiners who knew the context of the case. Twelve of the 17 concluded that the suspect who was prosecuted and convicted had no relation to the DNA found in the sample. Not only does this show that subjectivity occurs due to the context of the case, but the 17 examiners came up with different findings based on their past experiences meaning that not all DNA analysis is objective. Some organizations like the Scientific Working Group on DNA Analysis Methods say that quantitative statistical evidence should be presented with every categorical conclusion, but the US doesn’t require this (Dror and Hampikian).

False Positives:

There are two categories that cause wrongful identification in a DNA report: coincidental matches and false positives. Coincidental matches are DNA matches between two unrelated people. The probability of these matches is about 1 to 500,000 for white individuals and about 1 to 350,000 for black individuals. This small probability of coincidental matches makes people feel confident in DNA evidence. False positives, on the other hand, are matches between DNA and test DNA that result from issues in the forensics lab. There have been multiple cases of forensics labs accidentally switching victim and suspected rapist DNA which lead to convictions that were later overturned when the lab realized the error. There are also cases of misreading or misunderstanding a sample. In a case from 1993, a man was convicted of rape because someone interpreted a mixed sample of victim and perpetrator DNA as an individual sample. The conviction was again overturned. To prevent false convictions, retesting DNA is allowed, but it’s not an efficient solution. Many people are pushing for statistical information on the probability of false positives, so that the jurors can make accurate judgements based on DNA evidence (Thomas et al.).  

Conclusion:

DNA analysis is a useful tool for the criminal justice system, but subjectivity can be an issue in forensic testing. To combat wrongful convictions, there are organizations like The Innocence Project who use DNA testing to free the innocent, but reformed forensic testing standards should be put in place to prevent subjectivity and to ensure juries are correctly informed during trials. https://www.innocenceproject.org/    

Citation:

Augustyn , Adam, et al. “DNA Finerprinting.” Encyclopedia Britannica , 26 Apr. 2018, www.britannica.com/science/DNA-fingerprinting#ref153186. Dror, Itiel E., and Greg Hampikian. “Subjectivity and Bias in Forensic DNA Mixture Interpretation.” Science & Justice, vol. 51, no. 4, 2011, pp. 204–208., doi:10.1016/j.scijus.2011.08.004. Jobling, Mark A., and Peter Gill. “Encoded Evidence: DNA in Forensic Analysis.” Nature Reviews: Genetics, vol. 5, no. 10, Oct. 2004, pp. 739–751., doi:10.1038/nrg1455. Thompson, William C, et al. “How the Probability of a False Positive Affects the Value of DNA Evidence.” Journal of Forensic Sciences, vol. 48, no. 1, Jan. 2003, pp. 1–8., doi:10.1520/jfs2001171.