Case Study

Introduction

A MedTech company approached HydraTech to help them build a next-generation cuffless smart watch capable of measuring blood pressure, SpO₂, and heart rate continuously while remaining comfortable enough for all‑day wear. The device had to look and feel like a consumer smartwatch while quietly meeting medical‑grade expectations behind the scenes.

We partnered from early architecture through EVT/DVT, covering electronics, enclosure design, firmware, and system validation so the client could focus on clinical workflows and go‑to‑market.

Technologies & Solutions

• Developed a compact wearable PCB with high‑sensitivity PPG sensor, low‑power MCU, BLE 5, and secure storage.
• Implemented an event‑driven firmware architecture with aggressive duty‑cycling to extend battery life.
• Tuned signal‑processing pipelines on-device to clean PPG signals and extract robust features for BP estimation.
• Designed a sealed, injection‑moldable enclosure and strap interface optimized for both comfort and signal quality.

Horse Health Remote Monitoring System

Introduction

An equine health company wanted to move from periodic barn check‑ins to a full remote monitoring platform for horses. The goal was to continuously capture vital signs in the field and give veterinarians a real‑time view of risk, without overwhelming them with raw sensor data.

HydraTech was brought in as the engineering partner to design the wearable sensor hardware, low‑power firmware, and connectivity layer, while the client focused on veterinary workflows, regulations, and commercialization.

HydraTech’s Solution for the System

• Multi‑parameter Vital Monitoring: Designed a compact, rugged PCB around a low‑power ARM MCU, optical and motion sensors, and temperature sensing to capture a rich set of physiological and activity signals from the horse.
• On‑device Signal Processing (TinyML): Implemented on‑device filtering and lightweight ML models to clean data, detect anomalies, and surface features that feed higher‑level risk scores in the cloud dashboard.
• Robust Data Security: Applied modern encryption (at rest and in transit), secure boot, and signed firmware images to protect data from barn to cloud.
• End‑to‑end System Integration: Integrated the wearable, mobile gateway app, and veterinarian web portal so device events, alerts, and history stay in sync across devices.
• Resilient Connectivity: Used BLE 5.0 for device‑to‑phone links and Wi‑Fi / cellular via the phone or barn gateway for reliable cloud connectivity even in rural environments.
• Herd‑level Insights: Designed data models so care teams can track trends and risk across a herd, not just a single animal.

System Outcomes

• Earlier Intervention: Vets receive earlier warnings about deteriorating horses, enabling faster treatment and more personalized care plans.
• Actionable Alerts: Threshold‑based and trend‑based alerts help teams prioritize attention and escalate true emergencies quickly.
• Reduced Barn Visits: Remote monitoring reduces unnecessary in‑person checks while still keeping horses under continuous supervision.
• Scalable to More Herds: The same platform can be rolled out to new barns and programs without re‑engineering the core technology stack.

Conclusion

By combining low‑power embedded design, TinyML‑powered signal processing, and a secure, cloud‑connected architecture, HydraTech helped the client turn their equine monitoring concept into a deployable platform that improves outcomes for both horses and the teams who care for them.

Interior Lighting Kit For Camping

Introduction

An outdoor and overlanding brand needed a mobile-controlled interior lighting system for campers, vans, and RVs—allowing users to set brightness, color temperature, and scenes from their phone via Bluetooth, without running wires or relying on built‑in switches.

HydraTech delivered the cross‑platform mobile app and BLE firmware integration so the client could ship a cohesive lighting kit that feels intuitive in the field and stands up to off‑grid use.

Technologies & Solutions

• BLE Device Control: Implemented a reliable BLE connection manager with scanning, pairing, and automatic reconnection so lights stay controllable even after phone sleep or range drop.
• Intuitive UX: Designed flows for device discovery, brightness/color control, and preset scenes so campers can adjust lighting quickly from inside the tent or vehicle.
• Dashboard & Settings: Built in-app dashboards for managing multiple lights, firmware updates, and battery status where applicable.
• Cross‑platform: Delivered a single codebase targeting both iOS and Android for consistent experience across user devices.

Achievements & Impact

The lighting kit launched with strong adoption among campers and overlanders. The app reduced support tickets, improved user confidence in setup and daily use, and gave the client a scalable foundation for future connected outdoor products.

AI in Medical Devices

Introduction

A digital health company needed to run AI-based analysis on biosignals directly on their medical device—reducing latency, preserving privacy, and enabling use in low-connectivity or offline settings while keeping a path to regulatory compliance.

HydraTech partnered on the embedded ML pipeline, model optimization, and integration with the device firmware and cloud backend so the client could focus on clinical validation and product rollout.

Technologies & Solutions

• On‑device Inference: Deployed lightweight, quantized models on the device MCU or NPU to analyze biosignals in real time with minimal power and no dependency on the cloud for core detection.
• Model Optimization: Converted and tuned models for embedded constraints (memory, latency, accuracy) using edge ML toolchains while preserving clinical relevance of outputs.
• Firmware Integration: Wired the inference pipeline into the existing firmware with clear fallbacks, versioning, and telemetry to support validation and post-market monitoring.
• Dashboard & Workflows: Integrated device outputs with cloud and mobile dashboards for visualization, alerts, and clinician review in line with medical-device workflows.

Achievements & Impact

The medical device now runs AI-based analysis on-device with low latency and strong privacy. Clinicians get timely, interpretable outputs while the architecture supports validation and regulatory documentation for market clearance.

ECG Monitoring Systems

Introduction

A medical device company needed a reliable ECG monitoring solution for clinical and at‑home use—capturing clear cardiac signals, streaming data to a cloud or mobile dashboard, and meeting usability and compliance expectations for healthcare settings.

HydraTech partnered on the hardware design, signal conditioning, firmware, and connectivity so the client could focus on clinical validation, regulatory path, and go‑to‑market.

Technologies & Solutions

• ECG Front‑end & Signal Quality: Designed low‑noise analog front‑end, proper lead configuration, and filtering to deliver clean ECG waveforms suitable for diagnosis and algorithm input.
• Compact & Wearable Form Factor: Balanced electrode placement, comfort, and cable management for both spot checks and longer monitoring sessions.
• Firmware & Connectivity: Implemented data acquisition, buffering, and BLE/Wi‑Fi streaming to companion apps and cloud backends with configurable sample rates and formats.
• Dashboard & Alerts: Integrated with web and mobile dashboards for real‑time waveform display, trend views, and configurable alerts to support clinicians and patients.

Achievements & Impact

The ECG monitoring system delivers reliable capture and streaming of cardiac data, supports both clinical and remote monitoring workflows, and provides a solid foundation for further algorithm development and regulatory submissions.

Smart Ring for Continuous Vital Monitoring

Introduction

A digital health startup approached HydraTech to design a smart ring that continuously captures heart rate, SpO₂, skin temperature, and activity from the finger — a form factor with tighter size, thermal, and battery constraints than a wrist wearable, but with a richer optical signal.

We owned the electronics, mechanical, and firmware layers from concept through EVT, while the client focused on data science, mobile experience, and go‑to‑market.

Technologies & Solutions

• Miniaturized PCB: Designed a flex‑rigid PCB sized to a ring profile, integrating a low‑power MCU, BLE 5 SoC, PPG and temperature sensors, and secure storage.
• All‑day Battery Life: Implemented aggressive duty‑cycling, motion‑aware sampling, and BLE connection tuning to extend battery life across a full day of continuous monitoring.
• Signal Quality on a Curved Surface: Tuned LED drive, photodiode placement, and skin‑contact geometry to keep PPG signal robust under finger movement and ambient light.
• Mobile & Cloud Integration: Built BLE protocol, OTA firmware update, and companion‑app data sync so vitals stream cleanly from ring to phone to cloud.

Achievements & Impact

The smart ring delivers continuous, reliable vitals in a form factor users actually wear all day, giving the client a credible hardware foundation for their digital health offering.

Portable EEG Headsets

Introduction

A compact, wireless EEG headset built around the Qualcomm QCC5181, Nordic Semiconductor nRF52832, and Texas Instruments ADS1299 — engineered for real‑time audio and brainwave monitoring, tailored to neurofeedback applications.

The device is designed to advance neurotech and wearable health, packaging research‑grade biosignal capture into a form factor users can comfortably wear for full sessions.

Key Features

• End‑to‑end In‑house Development: Hardware, firmware, BLE, signal processing, and the companion mobile app are designed and integrated by HydraTech as a single, cohesive system.
• Built for the Neurotech Community: Suited to research teams, clinicians, and developers exploring neurofeedback — a foundation for collaborations and shared protocols.

Technologies & Solutions

• Audio & Connectivity (Qualcomm QCC5181): Low‑latency audio path and Bluetooth connectivity for synchronized stimulus delivery and streaming.
• BLE Host MCU (Nordic nRF52832): Manages session control, BLE 5 link to the mobile app, secure pairing, and OTA firmware updates.
• Biosignal Acquisition (TI ADS1299): 24‑bit, 8‑channel simultaneous‑sampling EEG front‑end with low‑noise PGAs for research‑grade brainwave capture.
• Real‑time Signal Processing: On‑device filtering, impedance monitoring, and feature extraction to give users immediate feedback on contact quality and session state.
• Companion Mobile App: Cross‑platform iOS / Android app for pairing, session control, live waveform display, and cloud sync.

Achievements & Impact

The headset gives the client a deployable, research‑grade platform for at‑home and field neurofeedback — with the signal fidelity, audio integration, and connectivity needed to support studies and ongoing therapeutic development.

Tool and Equipment

Introduction

These are some of the tools every embedded engineer should have to explore, debug, and optimize embedded systems. Together they cover the three workflows that decide whether a low‑power device ships on schedule or chases issues for weeks: firmware debugging, current and power measurement, and protocol‑level signal analysis.

The Toolkit

• J‑Link Ultra+ (SEGGER Microcontroller): Fast, reliable firmware flashing and source‑level debugging across ARM Cortex‑M and many other targets.
• Joulescope: Precise, wide‑dynamic‑range current measurement and power profiling — sleep‑mode microamps and active‑mode amps captured on a single trace.
• Nordic Power Profiler Kit II (Nordic Semiconductor): Power‑consumption analysis tuned for low‑power devices, with a built‑in programmable supply for nRF and other targets.
• Logic MSO (Saleae): Multi‑channel logic and analog capture for protocol analysis, timing, and signal debugging across SPI, I²C, UART, and more.

Why It Matters

With these tools, engineers can observe how firmware, hardware, and communication interact in real time — from stepping through code to measuring microamp‑level power consumption. Understanding real power behavior is critical when designing battery‑powered or energy‑harvesting devices, where every microamp matters.

Patient & Caregiver App for Smart Insole Monitoring

Introduction

A medical device client needed a connected‑care experience around their insole‑based monitoring device. We delivered a two‑app system: a Patient app that pairs the user's insole and streams biometrics, and a Caregiver app that gives clinicians or family members a dashboard for one or more monitored patients — with trends, alerts, and a "scan to help" sign‑in flow that lets a caregiver bring an elderly or impaired patient online without typing credentials.

Technologies & Solutions

• Two‑App Architecture: Separate Patient and Caregiver apps with role‑specific UX, sharing a common backend and consistent design system.
• Caregiver‑assisted Sign‑in: Caregiver scans a code or initiates a request to walk a patient through onboarding remotely — designed for users who cannot reliably operate a smartphone alone.
• BLE Insole Pairing: Reliable pairing flow with the smart insole, device‑info readouts, and resilient reconnection across background and foreground states.
• Vitals & Activity Visualization: Heart rate, step count, and aggregated health‑data views rendered as clean time‑series graphs for the caregiver.
• Caregiver Dashboard: Monitored‑patients list, per‑patient detail view, and a notification feed so caregivers can triage at a glance.
• Cross‑platform iOS & Android: Single codebase covering Bluetooth pairing, background sync, and OS‑level permissions on both platforms.

Patient Flow

Caregiver Dashboard

Achievements & Impact

The split Patient / Caregiver architecture lets the client serve users who cannot operate a smartphone unaided — the caregiver does the technical work once, and the patient just wears the insole. Vitals stream into a single dashboard the caregiver monitors at a glance, with notifications surfacing the moments that need attention.

IoT System with AWS

Introduction

Taking a connected device from a working prototype to a production fleet on AWS comes down to four building blocks: secure firmware updates, fleet provisioning, device‑state synchronization, and targeted job orchestration. The diagrams below capture the patterns we use on AWS IoT Core to ship ESP32‑class devices safely and operate them at scale.

1. OTA Firmware Updates (ESP32 + Amazon FreeRTOS)

The device runs Amazon FreeRTOS with an OTA agent. New firmware images are signed with an AWS Certificate Manager code‑signing certificate and stored in S3; AWS IoT Core creates an OTA job that the device picks up over MQTT. The agent verifies the signature with the device's private key before swapping from version 092 to 093 — so a tampered or interrupted image can never become active firmware.

2. Fleet Provisioning

Devices ship with a bootstrap certificate and request their production identity at first boot. The device presents its bootstrap cert plus a CSR; a custom Lambda validates ownership, IoT Core enacts the birth policy, signs the CSR, and returns the official certificate. A provisioning template then runs automatically — creating the Thing, attaching it to the right groups, and applying the production policy. Each unit ends up with a unique, revocable identity without any manual setup at the factory.

3. Device Shadow

Each Thing has a JSON shadow that holds desired and reported state. The device publishes its current state to deviceId/shadow/update; the cloud writes the desired state to the same topic, and the broker fans out a /update/delta message to the device so it knows what changed. The device acknowledges via /update/accepted. Apps and dashboards interact with the shadow rather than the device directly, so commands queue cleanly while devices sleep or roam.

4. Targeted Rollouts with IoT Jobs

Production rollouts target subsets of the fleet. We use dynamic groups — queried by shadow attributes such as firmware version or hardware revision — combined with a static "exclude list" group for canaries that should not receive a job. A Lambda function updates target shadow attributes so a rollout can advance ring‑by‑ring, and an IoT job carries the work to every matching device.

Why It Matters

Stitched together, these four patterns take a customer from a single‑device prototype to a fleet‑ready product on AWS — secure firmware updates, hands‑off onboarding, reliable state sync, and staged rollouts — without re‑inventing the cloud stack for every program.