Gesture Recognition with Edge AI

Classifying hand or body gestures from IMU (accelerometer + gyroscope) data. Models process short windows of motion data to recognize predefined gestures. Used for touchless control, wearable interfaces, and accessibility devices. Requires 6-axis or 9-axis inertial measurement unit.

Hardware Requirements

Minimum RAM 64 KB
Minimum Flash 512 KB
Sensor Inputs imu
Typical Model Size 20 KB (quantized int8)

Compatible Microcontrollers

Hardware Guides

Arduino Nano 33 BLE Gesture Recognition TFLite

Good

The Arduino Nano 33 BLE is a beginner-friendly option for gesture recognition with TFLite Micro. Its built-in 9-axis IMU (LSM9DS1) eliminate…

ESP32-C3 Gesture Recognition with Edge Impulse

Good

The ESP32-C3 runs gesture recognition models from Edge Impulse with low inference latency. Its 400 KB SRAM handles IMU classifiers with 5-10…

ESP32-C3 Gesture Recognition with TFLite Micro

Excellent

The ESP32-C3 is an excellent match for gesture recognition with TFLite Micro. 400 KB SRAM delivers 6.3x the 64 KB minimum while 160 MHz proc…

ESP32-C6 Gesture Recognition with Edge Impulse

Excellent

Espressif's ESP32-C6 excels at gesture recognition via Edge Impulse. The 1-core risc-v at 160 MHz with 512 KB SRAM handles 20 KB quantized m…

ESP32-C6 Gesture Recognition with TFLite Micro

Excellent

For gesture recognition, the ESP32-C6 with TFLite Micro scores Excellent. Its 512 KB internal SRAM (8.0x the required 64 KB) and 160 MHz clo…

ESP32 Gesture Recognition with Edge Impulse

Excellent

The ESP32 is an excellent match for gesture recognition with Edge Impulse. 520 KB SRAM delivers 8.1x the 64 KB minimum while 240 MHz process…

ESP32 Gesture Recognition with TFLite Micro

Excellent

For gesture recognition, the ESP32 with TFLite Micro scores Excellent. Its 520 KB internal SRAM (8.1x the required 64 KB) and 240 MHz clock …

ESP32-S3 Gesture Recognition with Edge Impulse

Excellent

Edge Impulse enables gesture recognition on the ESP32-S3 by training a classifier on IMU accelerometer and gyroscope data. Connect a 6-axis …

ESP32-S3 Gesture Recognition with TFLite Micro

Excellent

Espressif's ESP32-S3 excels at gesture recognition via TFLite Micro. The 2-core xtensa-lx7 at 240 MHz with 512 KB SRAM handles 20 KB quantiz…

i.MX RT1062 Gesture Recognition with CMSIS-NN

Excellent

NXP's i.MX RT1062 excels at gesture recognition via CMSIS-NN. The 1-core cortex-m7 at 600 MHz with 1024 KB SRAM handles 20 KB quantized mode…

i.MX RT1062 Gesture Recognition with TFLite Micro

Excellent

For gesture recognition, the i.MX RT1062 with TFLite Micro scores Excellent. Its 1024 KB internal SRAM (16.0x the required 64 KB) and 600 MH…

nRF52833 Gesture Recognition with Edge Impulse

Good

The nRF52833 handles gesture recognition effectively with Edge Impulse. 128 KB SRAM at 64 MHz provides 2.0x headroom over the 64 KB requirem…

nRF52833 Gesture Recognition with TFLite Micro

Good

The nRF52833 handles gesture recognition effectively with TFLite Micro. 128 KB SRAM at 64 MHz provides 2.0x headroom over the 64 KB requirem…

nRF52840 Gesture Recognition with Edge Impulse

Excellent

Nordic Semiconductor's nRF52840 excels at gesture recognition via Edge Impulse. The 1-core cortex-m4f at 64 MHz with 256 KB SRAM handles 20 …

nRF52840 Gesture Recognition with TFLite Micro

Good

Running gesture recognition on the nRF52840 with TFLite Micro is practical. 256 KB SRAM meets the 64 KB minimum with 4.0x headroom. The 64 M…

RA6M5 Gesture Recognition with CMSIS-NN

Excellent

For gesture recognition, the RA6M5 with CMSIS-NN scores Excellent. Its 512 KB internal SRAM (8.0x the required 64 KB) and 200 MHz clock ensu…

RA6M5 Gesture Recognition with TFLite Micro

Excellent

Renesas's RA6M5 excels at gesture recognition via TFLite Micro. The 1-core cortex-m33 at 200 MHz with 512 KB SRAM handles 20 KB quantized mo…

STM32F4 Gesture Recognition with Edge Impulse

Good

The STM32F4 classifies IMU gestures with Edge Impulse's optimized inference pipeline. The Cortex-M4F's DSP instructions handle spectral feat…

STM32F4 Gesture Recognition with TFLite Micro

Good

Running gesture recognition on the STM32F4 with TFLite Micro is practical. 192 KB SRAM meets the 64 KB minimum with 3.0x headroom. The 168 M…

STM32F7 Gesture Recognition with CMSIS-NN

Excellent

For gesture recognition, the STM32F7 with CMSIS-NN scores Excellent. Its 512 KB internal SRAM (8.0x the required 64 KB) and 216 MHz clock en…

STM32F7 Gesture Recognition with TFLite Micro

Excellent

For gesture recognition, the STM32F7 with TFLite Micro scores Excellent. Its 512 KB internal SRAM (8.0x the required 64 KB) and 216 MHz cloc…

STM32H7 Gesture Recognition with CMSIS-NN

Excellent

The STM32H7 is an excellent match for gesture recognition with CMSIS-NN. 1024 KB SRAM delivers 16.0x the 64 KB minimum while 480 MHz process…

STM32H7 Gesture Recognition with TFLite Micro

Excellent

For gesture recognition, the STM32H7 with TFLite Micro scores Excellent. Its 1024 KB internal SRAM (16.0x the required 64 KB) and 480 MHz cl…

STM32L4 Gesture Recognition with Edge Impulse

Good

STMicroelectronics's STM32L4 is a solid choice for gesture recognition using Edge Impulse. The cortex-m4f core at 80 MHz with 128 KB SRAM ac…

STM32L4 Gesture Recognition with TFLite Micro

Good

Running gesture recognition on the STM32L4 with TFLite Micro is practical. 128 KB SRAM meets the 64 KB minimum with 2.0x headroom. The 80 MH…

STM32U5 Gesture Recognition with CMSIS-NN

Excellent

The STM32U5 is an excellent match for gesture recognition with CMSIS-NN. 786 KB SRAM delivers 12.3x the 64 KB minimum while 160 MHz processe…

STM32U5 Gesture Recognition with TFLite Micro

Excellent

The STM32U5 is an excellent match for gesture recognition with TFLite Micro. 786 KB SRAM delivers 12.3x the 64 KB minimum while 160 MHz proc…

Industry Applications

Consumer Electronics Healthcare Gaming Industrial Control Wearables

Build Gesture Recognition with ForestHub

ForestHub compiles visual AI workflows to C code for your microcontroller. Choose your hardware, build your gesture recognition pipeline, deploy in minutes.