Bench Talk

New Tech Tuesdays

Join Mouser's Technical Content team for a weekly look at all things interesting, new, and noteworthy for design engineers.

The field of prosthetics is said to have begun thousands of years ago.^[1] However, traditional prosthetic devices still face limitations despite centuries of progress, most recently in materials, myoelectric control (i.e., electricity generated by muscles), and customization. Body-powered, cosmetic, passive, and mechanical prosthetics lack the precision, skill, and sensory feedback required for natural movements.

Even myoelectric prosthetics, while an improvement, rely on pre-programmed muscle contractions that feel unnatural and require training. In this week’s New Tech Tuesdays, we see how fundamental transformations in prosthetics are now emerging by integrating biometrics that offer seamless control and real-time responsiveness.

Biometric Feedback Enhances Control

Biometric feedback refers to the process in which sensory information is returned to the user from a prosthetic limb to mimic the natural sensory input received from a biological limb. With biometrics, the user can really “feel” and, therefore, control and manipulate objects.

Recent advancements in biometric technology are creating prosthetics that capture signals from muscle fibers or nerves. For example, electromyography (EMG) sensors detect electrical activity in muscles, while advanced tactile sensors simulate touch sensation.

Biometrics in Action

Incorporating biometric tech into prosthetics relies on components and systems that allow for real-time functionality, such as the following:

• EMG sensors: Detect and translate muscle activity. These sensors allow users to flex their prosthetic fingers or lift objects naturally.
• Tactile sensors: Provide sensory feedback by copying sensations like pressure and texture, allowing users to feel and adjust their grip strength in real time.
• Neural interfaces: Create direct communication between prosthetics and the nervous system for seamless control and natural movements.

One fascinating example of this technology is the LifeHand project, which combines sensors within a prosthetic hand that connects to the user’s nervous system. This technology enables users to experience touch sensations with the texture of objects and control their prosthetic hand with precision.^[2] In another case, the Massachusetts Institute of Technology (MIT) and Boston’s Brigham and Women's Hospital have developed a bionic leg that uses nerve signals to stimulate faster, more natural movement.^[3] Additionally, a 2024 study showed that subjects using a myoelectric interface increased their walking speed by up to 41 percent.^[4]

Prosthetics Reimagined

Biometrics addresses the gaps in fluidity and responsiveness associated with traditional prosthetics. These prosthetics are already reshaping the future of mobility and agility in a few ways:

• Biometric systems allow for smoother walking and better weight distribution so users can move more naturally on different surfaces.
• Tactile sensors provide real-time feedback so users can perform tasks that demand fine motor skills, like writing or typing (Figure 1).
• Advanced prosthetics use artificial intelligence (AI) to predict user intent.

Figure 1: An advanced prosthetic arm offers precision and adaptability as it seamlessly integrates technology into everyday tasks. (Source: Gorodenkoff/stock.adobe.com)

Longevity is another advantage of biometric prosthetics. Lightweight designs and compact biometric sensors create more comfortable and accessible prosthetics so users can wear them longer.

Combining biometrics with AI and wearable tech is opening doors in the field. MIT’s bionic leg, for example, incorporates neural feedback to adjust to a user’s walking speed and style.

The Newest Products for Your Newest Designs^®

This week’s New Tech Tuesdays features the STMicroelectronics ST1VAFE6AX biosensor with a machine learning core (MLC). Designed to detect motion and body signals, the ST1VAFE6AX incorporates a virtual analog front-end (vAFE) channel for biopotential signal detection and a six-axis inertial measurement unit (IMU) for motion tracking. The synchronous signals from the vAFE and IMU enable on-chip, context-aware analysis at the edge. The sensor’s MLC offers exportable features and filters to enable AI applications.

Tuesday’s Takeaway

Biometric feedback doesn’t just set the stage for better prosthetics; it brings an opportunity to change the lives of people who need them. These intuitive systems with sensory perception help bridge the gap between humans and machines, resembling the change we expect after centuries of prosthetics. With these advancements, individuals are empowered to regain mobility and, more importantly, a sense of independence.

Sources

[1] https://magazine.medlineplus.gov/article/prosthetics-through-the-ages
[2] https://www.faulhaber.com/en/motion/prosthetics-lifehand/
[3] https://news.mit.edu/2024/prosthesis-helps-people-with-amputation-walk-naturally-0701
[4] https://www.nature.com/articles/s41591-024-02994-9