Firmware for a Custom Skin Cancer Screening Device

Detects malignant skin growth without a biopsy

Linux

C++

Solution FPGA-based LED-enabled device providing accurate assessment of suspect skin growth

Industry

Healthcare
Software and Technology

ENGAGEMENT MODEL

Fixed Price

METHODOLOGY Waterfall

Team

Firmware Developers
QA Lead
Business Analyst

QA Engineer
Project Manager

Veriskin, a medical device company specializing in skin cancer screening, wanted to launch a custom handheld gadget that helps physicians and non-experts determine whether a suspect skin lesion is cancerous without an invasive biopsy.

Softeq developed firmware components for the device and helped the client test the viability of their idea.

BUSINESS NAME Veriskin Inc.
LOCATION USA
BUSINESS ACTIVITY Technology-assisted healthcare delivery

Case Highlights

Softeq participated in the development of a complex Wi-Fi-enabled system equipped with powerful functionality.

Incorporates a FPGA-powered handheld device based on the Qualcomm Snapdragon SD410 processor
Is driven by embedded software
Includes hardware components such as an audio speaker, accelerometer, and display
Captures LED light signal variations and translates them into a visual diagram in real time
Monitors the vascular refilling rate and proceeds with a custom algorithmic data analysis

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Problem

Veriskin decided to build a novel device that uses Machine Learning algorithms for non-invasive skin cancer detection.

They turned to Softeq to test the viability of their idea through a proof of concept (PoC) and develop firmware components powering the device.

Overview

The solution is a complex Wi-Fi-enabled system that incorporates:

A FPGA-powered handheld device based on the Qualcomm Snapdragon SD410 processor complete with LEDs
Embedded software
Hardware components: audio speaker, accelerometer, and display (among others)

Equipped with 2 photodetectors and a force sensor, the solution captures LED light signal variations and translates them into a visual diagram in real time.

To diagnose the suspect lesion’s condition, the system monitors the vascular refilling rate and proceeds with a custom algorithmic data analysis complete with a plain report output on the UI.

Firmware and Software Functionality

Audiovisual guide with error messaging
Calibrated LED lights maximizing photodetector sensitivity
Memory capacity for 100+ test results downloadable via USB or BLE
Custom Linux BSP and drivers
Built-in flash memory-based software
Optimized Linux boot-time
Firmware updates via the USB
Secure login (SSH protocol)

Project Outcomes

The resulting solution was expected to participate in rigorous clinical testing across US dermatological institutions. The system showed the capability of detecting malignant skin growth without extra biopsies or examinations. The device was meant to cut healthcare-associated costs by providing a low-cost and prompt cancer diagnostics method.