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Our Mudra platform contains strong advantagesleads the way in sensors technology, human centered design, natural and intuitive interaction, and tailored gestures.

Through our ability to process large- scale anonymized data from cloud-based calibrations and mobile apps, we are building a large database of finger and hand gestures. This will allow us to gain unparalleled exceptional insights on trends, behaviors, and usage, across the world, under a large variety of users’ physiology. Our real-time efficient algorithms run on the edge-device itself without a need for cloud-based computing.



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Our hardware pillar includes the device form factor, electrodes, sensorssensors, and miniaturized flex - rigid electronics.

Form factor research includes determining the device design – (capsule, bracelet, wristband,
watch band) – and modeling the curvature of the band to snuggly fit the wrist area snuggly,
and feel pleasant and comfortable to be worn on daily basis. It also includes the serial over-mold manufacturing process to ensure high yield production.



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Electrodes research includes the and development of electrode materials and geometry to
achieve a durable electrode that sustains its physical properties on the wrist’s skin contact, and
endures thousands of wear/off cycles.

Our proprietary Surface Nerve Conductance (SNC) sensors are developed specifically for the
inner wrist area; therefore, they can sense low energy biopotentials and maintain optimal
bandwidth and minimize external interference sources.


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We Our develop miniaturized flex-rigid electronics design and manufacturing offer a flexible
shell with semi flex-rigid printed circuit board, to meet strict bill of materials and design for
assembly requirements, and consumer laws.

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Our software pillar includes a cross platform software engine, artificial intelligence learning algorithms, and software applications.

We developed a unique cross-platform software engine, which supports real-time signal
processing and is capable of cross-platform algorithms mitigation on multiple operating systems.
This allows us to run our software on low compute power wearables and digital devices, and to
mitigate algorithms across platforms without the need to re-write the algorithms for each
operating system.


Our machine learning algorithms as well as deep learning neural networks AI architecture leverage the most advanced approaches of few-shot learning algorithms, making classification based on a very small number of samples, on a unique bio-signal for which we create the unique, non-available training and validation sets. We achieved over 96% accuracy with a very short calibration procedure for multiple users.

We develop software applications for mobile and desktop operating systems which integrate the algorithms and supply the users with the desired gestures and functions.


Our humanware and user experience pillar includes the hand and finger gestures that the user performs, and the functions that bind with these gestures, to input commands and to control devices.

We developed a set of gestures that create a natural interaction and are optimized for humans rather than for computers. As a result, users integrate naturally and seamlessly into controlling their devices.

Our gestures include discrete gestures, continuous gestures, and air-touch gestures:

Discrete gestures.

Moving a single finger or a soft finger tap, e.g. moving the index finger, or tapping the index finger on the thumb. This can be used for select, go back.

Continuous gestures. Applying fingertip pressure, e.g. apply pressure between the index and the thumb. This can be used for swipe, scroll, drag and drop.


Moving and controlling a pointer (cursor location) by moving the wrist in mid-air to a desired location.


Combining a sequence of a discrete gesture, a continuous gesture, and air-mouse, e.g. a soft tap of the index on the thumb, then applying fingertip pressure, and moving the hand to the right. This can be used as a “slide-to-lock” gesture.

Each customer of ours may require different bundles of hardware, software, and humanware solutions, with integration interfaces for its device, system, and design.

We specifically tailor the set of gestures to each controlled device and scenario, as we deeply believe each device’s form factor and user input should be tailored specifically to the user’s intent, rather than having a set of pre-defined gestures for all devices and functions.

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