News & Insights
FPAA Wearable Heart Monitoring Without Heavy Power Use
FPAA technology enables real-time heart monitoring in wearable systems by shifting signal processing into the analog domain, removing the need for power-intensive digital pipelines. Cardiac features are extracted continuously at microwatt to nanowatt power levels, supporting always-on operation. This approach points toward wearable physiological monitoring with dramatically reduced energy consumption.
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How to Prototype Faster with FPAA Development Boards
Analog prototyping is slow due to component variation, layout effects, and repeated hardware iterations. FPAAs speed this up by using pre-characterized analog blocks that are configured in software.
With FPAA development boards, engineers can adjust filters, gain, and signal paths instantly without redesigning hardware. This makes analog iteration faster, more repeatable, and less dependent on PCB revisions.
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FPAA vs. Discrete Op-Amp Networks: When Simpler Is Actually Harder
Discrete op-amp circuits are easy to design but often require multiple hardware iterations due to layout effects, tolerances, and real-world deviations. This can make convergence slow and unpredictable. FPAAs move much of this iteration into reconfiguration, improving repeatability and reducing sensitivity to PCB and component variation. Discrete designs still fit fixed, high-precision cases, but FPAAs offer faster iteration and more adaptable system behavior.
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Re-Architecting Edge AI at the Sensor Boundary with FPAA
Re-architect Edge AI at the sensor boundary. See how FPAA analog feature extraction reduces over-digitization and improves system-level efficiency.
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Building a High-Sensitivity EKG with the Okika FPAA Sing1
Explore a hands-on experiment using the Okika FPAA Quad4 to unlock cleaner EKG signals and precise Wheatstone measurements through reconfigurable analog design.
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Building Energy-Efficient Neuromorphic Systems with FPAAs
Insights from Dr. Jennifer Hasler on neuromorphic hardware, analog computing, and how FPAA technology could dramatically reduce AI power consumption.
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Common First-Time FPAA Design Mistakes and How to Avoid Them
Engineers moving from digital FPGAs to FPAAs often run into unexpected analog behavior, including gain issues, clipping, noise, and imperfect filtering. Early mistakes usually come from applying digital assumptions, underestimating headroom, and relying too heavily on simulation. This article explains common first-project pitfalls and how disciplined gain planning, incremental testing, and measurement-driven iteration lead to stable FPAA systems.
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Integrating FPAA Designs with MCU and FPGA Systems
Most real systems combine analog and digital components, with FPAAs often working alongside MCUs and FPGAs. System stability depends on clearly defining what each device is responsible for: signal conditioning in analog, control in MCUs, and high-speed processing in FPGAs. Many integration issues arise from blurred boundaries, especially in timing, power, and signal interfaces.
Successful designs treat the FPAA–MCU–FPGA split as an architectural decision, not just a connectivity problem. Careful attention to interfacing, grounding, and latency ensures predictable behavior and avoids complex debugging later.
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Okika Devices Introduces Chameleon™ 8th Order Butterworth Lowpass Filter Family at DesignCon
Okika Devices today announced the introduction of 6 lowpass filter modules in the Chameleon™ family. Built on Okika’s FlexAnalogTM FPAA technology, the OTC931xL devices are pre-programmed lowpass filter modules engineered for demanding analog signal conditioning applications.












