A startup that built wearable gesture controllers is now using neural sensors to teach robots how to understand human movement and intent in real time. Wearable Devices Ltd., an Israeli AI wearables company, announced its first-half 2026 financial results and revealed a significant strategic shift: moving beyond consumer gesture recognition into Physical AI and robotics applications where traditional camera-based systems struggle.

The company generated $350,000 in revenue for the six months ended June 30, 2026, compared to $294,000 in the same period last year, driven by sales of its Mudra Link and Mudra Band wearable devices across iOS, Android, and desktop platforms. But the real story isn't the revenue growth; it's where the company is placing its bets for the future.

What Problem Are Neural Wearables Solving for Robots?

Traditional AI systems rely heavily on computer vision, cameras, and visual sensors to understand what's happening in the physical world. But cameras have blind spots. They can't see around corners, through occlusion, or in crowded environments where line-of-sight is blocked. Wearable Devices is proposing a different approach: use wearable neural sensors that read electrical signals from human muscles and nerves to give robots and AI systems a window into human intent before physical motion even occurs.

"Where vision-based AI fails due to occlusion or field-of-view limits, wearable neural sensing bridges the gap without cumbersome gloves," said Asher Dahan, Chief Executive Officer of Wearable Devices.

Asher Dahan, Chief Executive Officer of Wearable Devices

The company's approach centers on surface electromyography (sEMG), a non-invasive technique that measures electrical activity in muscles. By analyzing sEMG data from thousands of user interactions, Wearable Devices has built what it calls the Large MUAP Model (LMM), a physiology-based foundational model that serves as an intention-detection layer. Think of it as a biological signal translator that converts muscle activity into actionable digital commands.

How Is Wearable Devices Building Its Physical AI Strategy?

The company is launching two new hardware products designed specifically for robotics and extended reality (XR) applications:

• Mudra Pro: Features three sEMG channels, an inertial measurement unit (IMU) for motion tracking, and a photoplethysmogram (PPG) sensor for heart rate data, designed for advanced AI and XR programs
• Mudra Ultimate: Offers eight sEMG channels, IMU, PPG, and an integrated System-on-Chip for more complex enterprise applications requiring deeper neural signal analysis
• Mudra Studio: A software platform that lets developers build applications based on user intent, input, and raw neural signal data, with AI-powered "vibe coding agents" that replace traditional software development kit complexity with natural language prompts

These products represent years of feedback from both consumer users and enterprise clients, according to the company. The strategy is to use consumer B2C products like Mudra Link and Mudra Band to validate market demand and collect real-world data, then apply those insights to enterprise B2B offerings and robotics applications.

"Our growth strategy relies on an active build-measure-learn cycle driven by our consumer B2C offerings, including Mudra Link and Mudra Band. By delivering products directly to users, we collect critical real-world feedback," stated Asher Dahan.

Asher Dahan, Chief Executive Officer of Wearable Devices

The company also established ai6 Labs, an internal innovation engine that operates as a closed loop combining foundational neural research, rapid monetization, and an AI accelerator. This unit is designed to prototype agentic solutions and product architectures quickly, allowing the company to stay agile as AI technology evolves.

Why Does Intent Detection Matter for the Future of AI?

The core insight driving Wearable Devices' pivot is that traditional input methods, like keyboards, touchscreens, and even voice commands, fail to capture full human context. A person's intent often precedes visible action. By reading neural signals, AI systems could theoretically understand what a human wants to do before they physically do it, enabling faster, more intuitive human-machine interaction.

This has implications across multiple sectors. In clinical settings, the LMM is being explored for stroke rehabilitation, where understanding a patient's neural intent could help guide recovery. In industrial automation, wearable neural sensing could enable workers to control robotic arms or machinery with subtle muscle movements. In consumer XR, it could replace button presses and hand gestures with direct neural input.

The company also expanded its patent portfolio in 2026 to protect its core neural interface capabilities and gesture recognition technology, with patents that define gesture start and end points without requiring physical buttons. This intellectual property strategy positions Wearable Devices to defend its technological leadership across consumer XR, industrial automation, and assistive technology markets.

What's the Competitive Landscape for AI Wearables?

Wearable Devices is not alone in pursuing AI-powered wearables. Meta's Ray-Ban AI glasses and the Rabbit R1 have captured consumer attention with voice and visual AI features. However, Wearable Devices is taking a different technical approach, focusing on neural signal processing rather than visual or audio input. This differentiation could prove valuable in scenarios where cameras and microphones are impractical or where privacy concerns limit their use.

The company's dual-channel business model, combining direct-to-consumer sales with enterprise licensing, allows it to build brand awareness among consumers while generating revenue from industrial and robotics applications. This approach also creates a feedback loop: consumer products generate training data that improves enterprise solutions, which in turn validate the technology for larger-scale deployment.

As AI systems become more embedded in physical environments, the ability to understand human intent without relying solely on cameras or microphones could become a significant competitive advantage. Wearable Devices is betting that neural sensing is the missing piece in the AI wearables puzzle.