Independent Research · Leesburg, Virginia
ExoLab is a solo R&D lab run by Greg Klassen — a 30-year DSP engineer, retired CEO, and SCA3 patient — dedicated to building open exoskeleton control systems for neurological mobility conditions.
Real hardware. Real code. Real stakes.
Who is ExoLab
Greg Klassen spent three decades in digital signal processing — designing real-time filter architectures, tuning PID loops, and building embedded control systems from the ground up. He then spent years as a CEO, before a diagnosis of Spinocerebellar Ataxia Type 3 (SCA3) changed the plan.
SCA3 is a progressive neurological condition that attacks coordination, balance, and gait. Commercial exoskeletons exist — but none are designed for cerebellar ataxia, where the challenge is balance, not paralysis.
So Greg is building his own. Working from a six-acre property in Leesburg, Virginia, ExoLab is a one-man R&D operation applying 30 years of signal processing expertise to the hardest problem Greg has ever faced: getting himself back on his feet.
The lab pursues three goals simultaneously: personal mobility research, rigorous open documentation of the build process, and informed engagement with the commercial and investment exoskeleton landscape.
Current status: Phase 1 hardware on order. CubeMars AK80-9 actuators inbound. Software stack under development.
The Vision
What ExoLab is working toward: powered joint assistance for a person with SCA3-affected gait. These images represent the target, not the current state. Phase 4 is the goal.
// Placeholder images shown. Replace with actual ExoLab photos when available. Two slots reserved for your personal images.
Build Documentation
A five-phase roadmap from benchtop motor control to a wearable bilateral exoskeleton assist system. Built on 30 years of DSP experience. Click any phase for details.
One motor. One controller. Your own PID loop. The CubeMars AK80-9 delivers 9Nm rated / 22Nm peak torque through an integrated brushless motor, planetary gearbox, encoder, and CAN driver — all in a single package. The MIT Mini Cheetah protocol runs over CAN bus. Objective: command torque, read position, tune a real impedance controller.
| Component | Part | Cost | Notes |
|---|---|---|---|
| Actuator | CubeMars AK80-9 V3.0 | ~$500 | 48V, MIT CAN protocol, integrated encoder |
| CAN Interface | Waveshare USB-CAN-A | ~$22 | socketCAN on Linux, plug-and-play |
| Power Supply | MEAN WELL 48V 10A | ~$90 | Bench PSU — current-limited for safety |
| E-Stop | 22mm latching mushroom switch | ~$12 | Non-negotiable. Within arm's reach always. |
| Frame | 2020 Aluminum Extrusion | ~$50 | Rigid mount — 9Nm will move a light table |
| Controller | Raspberry Pi 5 or STM32G4 | ~$60 | Python CAN stack or embedded C |
Pure sensing. No actuation. Strap IMUs and force-sensitive resistors to both legs and walk — on carpet, on gravel, on the six-acre property. Capture what SCA3 gait actually looks like at 500Hz. This data becomes the training signal for every control algorithm written in Phases 3–5.
| Component | Part | Cost | Notes |
|---|---|---|---|
| IMU (×3) | ICM-42688-P breakout board | ~$30 ea | 32kHz sampling, significant upgrade from MPU-6050 |
| Force Sensors | Interlink 402 FSR (×8) | ~$6 ea | Heel, 1st/5th met head, big toe per foot |
| ADC | ADS1115 16-bit, I2C | ~$13 | 4-channel analog read for FSRs |
| MCU | Teensy 4.1 (600MHz ARM M7) | ~$30 | Real-time capable; DSP-friendly architecture |
| Storage | MicroSD module + 8GB card | ~$8 | Log raw data at 500Hz for offline analysis |
| Battery | LiPo 3.7V 2000mAh + TP4056 | ~$15 | Wearable power for walking trials |
Connect the motor to a 1:1 mechanical replica of a human knee. Drive it with gait data captured in Phase 2. When this mechanical leg tracks a walking cycle correctly — under impedance control — you are ready for Phase 4. Control loop latency target: under 5ms end-to-end.
| Component | Part | Cost | Notes |
|---|---|---|---|
| Frame | 80/20 1" aluminum extrusion | ~$100 | Vertical leg mock-up with pivot joint |
| Knee Pivot | Flanged pillow block bearing 12mm | ~$25 | Zero-backlash coupling to motor shaft |
| Load Cell | 50kg S-type + HX711 amp | ~$22 | Measure actual torque output, validate commands |
| Current Monitor | INA226 I2C power monitor | ~$10 | Real-time power consumption → battery sizing |
| Leg Segments | Aluminum flat bar 1"×1/4" | ~$20 | Thigh + shank fabricated from hardware store stock |
The first device that goes on a body. A powered knee orthosis using the AK80-9 to provide assistive torque — not walking for you, but assisting where your own muscles are already trying. Safety gate: Phases 1–3 must be complete with 4+ weeks of stable operation before this phase begins. Katia present for all wearable sessions. Dr. Rosenthal signed off.
| Component | Part | Cost | Notes |
|---|---|---|---|
| Second Actuator | CubeMars AK80-9 (left leg) | ~$500 | Bilateral is safer than unilateral for ataxia |
| Battery | 48V 20Ah wearable LiPo pack | ~$250 | Sized for 2hr walking sessions |
| Brace Frame | KAFO modified or custom carbon | ~$1,000 | Structural foundation for the actuator mount |
| RF E-Stop | Wireless kill switch handheld | ~$75 | In-hand at all times during walking trials |
| Safety Harness | Chest harness + overhead tether | ~$100 | Mandatory for first 20+ wearable sessions |
The full system: hip and knee actuation, left and right, with a unified control stack running gait phase detection from dual IMU/FSR sensor arrays. Four AK80-9 actuators. A full power electronics bay. This is what academic labs build with grad student teams. ExoLab will build it solo — which means it will take longer, and every decision will be deeply understood. Estimated timeline: 6–18 months beyond Phase 4.
| Component | Est. Cost | Notes |
|---|---|---|
| 2× Additional AK80-9 (hips) | ~$1,000 | Higher torque variant for hip flexion/extension |
| Power Electronics Bay | ~$400 | 48V BMS, current distribution, emergency cutoff |
| Bilateral Frame | ~$2,000 | Carbon fiber + aluminum hybrid structural frame |
| Central Controller | ~$200 | Jetson Nano or Teensy 4.1 — real-time gait FSM |
| Full Sensor Array | ~$300 | 6× IMU, 16× FSR, full bilateral coverage |
| Misc / Integration | ~$1,000 | 3D printing, machining, wiring, iteration |
⚡ DOWNLOAD FULL LAB PLAN — The complete ExoLab Build Plan document including detailed parts lists, control theory background, DSP mapping tables, workshop setup guide, and safety protocols is available as a Word document. Contact to request →
Technical Background
The translation from digital signal processing to exoskeleton control is nearly one-to-one. Every skill developed over a 30-year engineering career maps directly to the core challenges of robotic mobility.
Timeline
A realistic timeline. Each phase is independently satisfying and produces real, documented results. No phase is skipped.
Essential Reading
The foundational texts and repositories behind this build. Every resource here is free and directly applicable to the control problems ExoLab is solving.
Robotics Summit & Expo · Boston · May 27–28, 2026
Greg attended the Robotics Summit & Expo in Boston — the world's leading technical event for commercial robotics developers, produced by The Robot Report and WTWH Media. Tracking exoskeleton hardware, rehabilitation robotics, and commercial mobility devices.
// Raw session notes — unfiltered, from the floor. Not affiliated with WTWH Media.
Get In Touch
ExoLab welcomes connection from researchers, clinicians, engineers, investors, and anyone navigating a neurological mobility condition. This work is open and documented.