Custom electronics and firmware
Board and on-device software designed around the sensor and the power budget the use case allows.
- Sensor selection and integration
- Low-power firmware
- Wireless communication to apps and gateways
Medical wearables
Wearable devices for remote vital-signs monitoring.
Wearable devices and ambient sensors that follow frail and elderly patients. From custom electronics to the platform that reads the data.
Or write to us: info@ggtechnologies.sm
1997
the first project
18
years in manufacturing
900
workers in the study
Where we start
A wearable is a chain, not a device.
The chain starts at the sensor and ends when a doctor or a coach acts on the reading. If one link is weak — battery life, signal quality, the way the data reaches the person who has to read it — the device ends up in a drawer.
We design the whole chain. Electronics and firmware on one side, the platform that collects and processes the data on the other. We have built wearable solutions for vital-signs monitoring in both healthcare and sport.
Healthcare
Monitoring of patients and the elderly, with data readable by those who provide care.
Sport
Athletes' physiological parameters, captured continuously during activity.
Technology
Our DigiSense® framework is the base for data acquisition and processing.
What we build
From the sensor to the dashboard, one project. Worn or in the room.
Remote-monitoring platforms
Where device data becomes readable: continuous collection, thresholds, alerts and history for the doctor, coach or caregiver.
- Continuous parameter acquisition
- Threshold and anomaly alerts
- Interfaces for operators and for patients
Physiological signal processing
Biological signals are noisy and voluminous. We clean them up, bring them all to the same scale so they can be compared, and store them so they can be searched.
- Signal cleaning and normalisation
- Time-series storage
- Analysis and models on the collected data
Ambient monitoring
Some measurements live in the room. Sensors in the home that follow the environment and the routines of frail and elderly patients, and that work on their own.
- Ambient and home sensors
- Detection of changes in daily routine
- Alerts to family and care staff
How we work
The parameter comes first. The technology comes last.
01
Define the parameter
Which reading you actually need, how often, and who reads it. A mistake here can only be fixed later with a new board.
02
Design the device
Sensor, power budget, form factor and data platform are chosen together: they constrain each other.
03
Prototype and field-test
Prototype, firmware, platform and field trials with the people who will use the device.
04
Move to production
Production rollout, maintenance and evolution over time.
FAQ
Frequently asked questions
Do you handle the hardware too, or only the software?
Both. We design custom electronics and firmware, and the platform that collects and processes the data. They are two halves of the same project: separating them is the fastest way to end up with a device nobody uses.
What is the difference between a medical and a sports wearable?
The requirement, not the technology. In sport, continuity of measurement under effort matters; in healthcare, data reliability and traceability of who consulted it matter. Design choices change, the skills do not.
Can you work on an existing device?
Yes. Often the hardware already exists and what is missing is the platform that makes the data usable, or the firmware needs reworking to cut power draw. We start from what is already there.
Does the device end up certified as a medical device?
A notified body signs the marking, and the path starts from the device class. We design the electronics, the firmware and the platform inside that path: classification, documentation, software development to the relevant standard. The first thing we tell you is which class your case falls into — often it sits outside the medical perimeter altogether, and the quote changes accordingly.
Where does patient data end up?
Wherever you decide. We also build architectures where processing stays on your own servers and the data never leaves your infrastructure — the same principle Podz.AI is built on.