Why Limb Interfaces May Beat Brain Implants to Market
- Dominic Borkelmans
- 23 hours ago
- 4 min read
Phantom Neuro just opened a patient registry for amputees, clinicians, and rehab teams, a small web form that signals a much larger shift. It follows a $19 million Series A led by Ottobock in April and fresh support from DARPA’s Commercial Strategy Office last September. While most of the attention in neurotech pools around brain implants and headline-ready BCIs, Phantom is pushing a different layer of the interface: muscle-level implants designed to give prosthetic hands more natural control.
More than two million people in the US live with limb loss, and between 20 and 40 percent of those who receive advanced prosthetic arms ultimately abandon them. Devices that look sophisticated on paper often feel awkward, inconsistent, or tiring in real use, pushing many back to body-powered hooks. Limb interfaces may sit outside the usual BCI spotlight, but they represent one of the clearest opportunities in neurotech: restore natural limb control and the market responds immediately, both in adoption and commercial impact.
Phantom Neuro’s Move Toward Trials
Phantom’s new patient registry is designed to connect amputees, clinicians, and rehab centers to upcoming studies, a step companies take when they are preparing for first-in-human work and need a real participant pipeline. It also helps shape early datasets before implants enter the clinic. The launch follows Phantom’s FDA Breakthrough designation, a signal that its regulatory path is becoming more defined as it moves toward first-in-human trials.
Phantom Neuro was founded by neurosurgeon Dr. Connor Glass to develop an interface layer, rather than a prosthetic hand. The company builds small under-skin electrode arrays that read intent signals from residual muscles, paired with an AI decoder called Phantom X. That signal then plugs into existing prosthetic hands from major manufacturers, acting as the control system rather than the hardware itself. Early validation comes from the ASCENT study, a non-invasive proxy test that reached about 94 percent accuracy across 11 hand and wrist movements after roughly ten minutes of calibration, with lower latency than typical surface-based control.
In April 2025, Phantom raised a $19 million Series A led by Ottobock, the world’s largest prosthetics manufacturer, bringing total funding to roughly $28 million. Ottobock’s involvement offers both credibility and a direct route into commercial hand ecosystems, since Phantom’s interface is meant to sit on top of hardware OEMs already produce. DARPA’s Commercial Strategy Office added about $300,000 in support, signaling dual-use interest. Together, these backers give Phantom a blend of strategic and institutional support rare for early-stage neurotech.
The Limb Interface Market
Around 2.3 million people in the US live with limb loss, with upper-limb amputations making up a smaller share but carrying a disproportionate impact on work, independence, and daily function. Globally, the numbers climb into the tens of millions as diabetes, vascular conditions, trauma, and cancer continue to drive incidence. Upper-limb loss remains the more technically challenging category, but it is also where better control translates most directly into quality-of-life gains.
Across that population, abandonment rates for advanced prosthetic arms remain high. Depending on the cohort, 20 to 35 percent of users eventually stop using upper-limb devices, and some studies place rejection closer to 50 percent when systems are heavy, slow, or difficult to control. Many people revert to body-powered hooks because the alternatives feel unintuitive, unreliable, or too cognitively demanding for everyday tasks. In practice, a significant share of amputees choose to live one-handed rather than adopt devices that do not behave the way their own hands once did.
Today’s solutions fall into a few main categories. Body-powered devices provide dependable but coarse control through harnesses and cables. Surface-based myoelectric systems offer pattern recognition and multi-articulated hands such as the i-Limb, Bebionic, and Michelangelo, yet often struggle with signal noise, slow response, and inconsistent control in real-world settings. Targeted muscle reinnervation improves signal sources but still depends on surface electrodes that can drift with sweat, motion, or sleeve pressure. The gap between current tech's promises and everyday functions leaves openings for approaches that deliver finer control, faster response, and far less cognitive load, precisely where implanted muscle interfaces aim to operate.
A handful of companies and labs are tackling different parts of that stack. Coapt focuses on advanced pattern-recognition controllers for surface EMG. Psyonic and Esper build the hands themselves, layering AI features on top. MIT’s biomechatronics groups, the Cleveland Clinic, and the KobrA project push research on sensing and actuation. Peripheral nerve interfaces from teams at the University of Michigan, Ripple Neuro, and Blackrock explore deeper signal sources, while BIOS positions itself at the neural-input-output layer. Phantom’s approach sits in its own category, more stable and precise than surface EMG, yet far less invasive than full nerve implants.
Even with clear unmet need, limb interfaces attract far less attention than cortical BCIs. Speech decoding and brain-controlled robotics dominate headlines, while upper-limb loss is treated as too small a market to shape the broader neurotech story. The hardware burden also discourages investors who prefer software-led plays. But unlike many neurotech categories, prosthetic control sits inside an established reimbursement system, and the clinical endpoints are unambiguous. That alignment between payers, regulators, and prosthetic manufacturers makes this space one of the most realistic paths to near-term impact.
Where Limb Interfaces Lead
Over the next decade, several forces are converging in ways that make limb-level interfaces far more viable than they were even a few years ago. Machine-learning models for biosignal decoding have matured, implantable hardware has become smaller and lower-risk, and major prosthetic manufacturers are actively looking for better control layers to pair with their existing hands. Policy shifts in disability tech are also pushing toward devices that support independence rather than cosmetic function alone. These trends give companies like Phantom a transparent path to the kind of everyday neurotech that slots into real patient settings.
If systems like Phantom's interfaces prove themselves, their impact stretches well beyond amputees. The same control layer could support stroke rehabilitation, industrial exosuits, or more natural human–robot interaction, where intent decoding becomes a bottleneck. Limb interface could occupy a space between classical brain-computer interfaces and robotics, a category built on peripheral neural signals rather than cortical implants. And if that control layer holds up in practice, limb interfaces could stand among the first neurotech systems to move into everyday use.
