Synaptics Fs7605 Touch Fingerprint Sensor With Pureprint-tm- Top [updated] Site

Synaptics FS7605 — Overview Report

3. Technical Reference / Integration Guide (NDA required – but you can request)

Actual paper title you want to request:

Synaptics FS7605 Fingerprint Sensor with PurePrint™ – Hardware Integration Guide v1.x

Contents:

How to request (if you are an engineer/buyer): Synaptics FS7605 — Overview Report 3

  1. Go to Synaptics’ “Contact Support” page.
  2. Select “Touch & Fingerprint Sensors” → “FS7605”.
  3. Request the Datasheet, Integration Guide, and Firmware API Reference.
  4. Provide a company email (Gmail will be rejected). Sign an online NDA.

10. Comparison with Competing Sensors

| Feature | Synaptics FS7605 | Goodix GF5288 | Fingerprint Cards FPC1540 | |---------|------------------|---------------|----------------------------| | On-chip MCU | ARM M4 @ 64 MHz | RISC-V @ 96 MHz | ARM M0 @ 32 MHz | | Anti-spoof | PurePrint™ (hardware) | Software only | Optional external | | Liveness latency | 120 ms | >250 ms | N/A | | Max templates | 10 | 5 | 8 | | Security cert | FIDO2 L2 | FIDO2 L1 | None |

6. Power Management

The FS7605 is optimized for battery-powered devices with three power modes:

| Mode | Current | Condition | |------|---------|------------| | Active (capture + match) | 22 mA (typical) | Full operation | | Idle (waiting for finger) | 1.2 mA | Periodic scanning at 5 Hz | | Sleep | 8 µA | No finger detection, RTC wakeup | Contents:

Wake-on-finger uses a low-power capacitive proximity sensor (integrated) drawing 15 µA, enabling always-on detection.

4.1 Conventional vs. TMR Top Stack

Traditional fingerprint sensors require a separate mechanical button or touch layer above the sensor, increasing Z-height and decoupling touch detection from fingerprint acquisition.

TMR Top integrates a transparent (invisible) touch-sensing mesh directly above the fingerprint pixels, using a thin-film metal-resistor layer. the sensor captures raw data. Simultaneously

Stack diagram (from finger to silicon):

Finger
   ↓
[Cover lens / glass] – 0.2 mm (optional)
   ↓
[TMR Top layer] – Integrated mutual‑capacitance touch electrodes (pitch ~200 µm)
   ↓
[Fingerprint pixel array] – 50 µm pitch capacitive plates
   ↓
[Analogue front-end + shield layer]
   ↓
[Silicon substrate]

3.3 Benefits vs. Host-based Liveness

| Aspect | Host CPU Liveness (e.g., software) | PurePrint™ on FS7605 | |--------|--------------------------------------|------------------------| | Data exposure | Raw fingerprint image to OS | Only binary accept/reject | | Anti-hacking | Vulnerable to OS-level interception | Secure enclave – no bus access to raw frames | | Speed | 100–300 ms (depends on CPU load) | 25 ms fixed | | Power | High (wakes application processor) | Low (dedicated NPU core) |

5. Maintenance (PurePrint™ Technology)

Because this sensor uses optical/Patterned Light technology (PurePrint), it requires a clean surface to work correctly.

How PurePrint Works

  1. Neural Network Classification: The FS7605 integrates a dedicated neural processing unit (NPU) directly on the sensor die. When you place your finger, the sensor captures raw data. Simultaneously, the PurePrint engine analyzes the image for artifacts of "fake-ness"—air bubbles in silicone, unnatural reflectivity in gelatin, or pixel regularity in printed images.
  2. Spoof Detection: The system has been trained on millions of fake fingerprints (printed, molded, gelatine, Play-Doh, and latex). It distinguishes between the natural electrical impedance of live skin (which has moisture and salt) vs. the uniform impedance of synthetics.
  3. Local Processing (The TOP Security): Crucially, all of this analysis happens inside the sensor chip. The host processor (CPU of the phone or laptop) never sees the raw fingerprint image. The chip sends back only a "Yes/No" token via the Trusted Output Protocol. This prevents malware on the PC from intercepting your biometric data.
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