About

the device

Knee

sensors

Non-invasive knee sensors for easy and secure placement by clinicians on the patient's knee.

Secure placement

Algorithm analyzes, compares, and assesses the health of the knee.

A machine learning

The Neural Network alogrithm reads new data, compares it to the existing information and aims to learn from it in order to increase accuracy.

Neural network

Cartilage damage score that is dynamic, easy-to-use and may add important data to the clinical practice.

Accuracy

A noninvasive device listens to and analyzes the sound of the cartilage.

A listening device

The

terminal

Compact and convenient orthopedic measuring device for use by the physician in his or her own office.

In office convenience

A modern and sleek design intended to fit seamless into any physician's office or practice without being obtrusive.

Cutting-edge design

The sensors and diagnostic terminal are compact in size, allowing for easy storage and requiring a small space in the office.

Compact terminal

The

platform

The Kneevoice device will be built on a platform that creates the cartilage damage score and automatically reports the results for the physician’s review and analysis.

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POWER OF KNEEVOIVE

Who can use

the Kneevoice

The score offered by Kneevoice will be part of a general orthopedic examination and could even be used during a routine medical checkup as a way to detect early development of osteoarthritis.

Orthopedic surgeons / medical professionals

Physical therapists

Orthopedic surgeons / medical professionals

Physical therapists

How does

it work

Kneevoice’s patented knee sensors are easily and securely placed on the knee of the patient.

The physician fills in the patient’s information such as:

The platform shows the number of knee movements being performed.

The patient performs 8–10 knee flexions.

Kneevoice records the noise generated by the joint, with the sensors capturing vibration and position.

Both the patient and the physician can listen to the sound of the knee, which gives a sign of the status of the knee’s health.

Listen to the knee:

The collected data will be transmitted to the cloud for storage, analysis and report generation. The neural network algorithm will not only compare the new data with existing information, but also aim to learn from it with the goal of increasing its accuracy with every measurement.

The data is collected and analyzed by the device, which automatically generates a score report indicative of cartilage status.

A report is automatically generated for sharing and clinical history purposes, and a sound recording is provided for further analysis.

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