Body Composition Analyzer SoC Solution

Body Composition Analyzer SoC Solution

Bio-impedance analysis (BIA) for accurate body fat, muscle mass, and hydration measurement with integrated high-precision AFE and advanced algorithms

Solution Overview

Body composition analysis using bio-impedance analysis (BIA) technology provides comprehensive health metrics including body fat percentage, muscle mass, bone mass, and hydration levels. Our solution integrates high-precision impedance measurement AFE, multi-frequency excitation, and advanced body composition algorithms, enabling accurate and repeatable measurements for home and professional use.

Application Areas

  • Smart body composition scales
  • Professional fitness assessment devices
  • Medical body composition analyzers
  • Multi-parameter health monitoring platforms

Application Block Diagram

Application Block Diagram
🎯

High Precision

24-bit Σ-Δ ADC with 1μV resolution, ENOB > 20 bits

Ultra-Low Power

Sleep current I_sleep < 1.5μA, extends battery life

🔧

High Integration

Built-in LCD driver, VREF, temp sensor - simplifies design

Core Features & Benefits

🎯

High-Precision BIA Measurement

24-bit ADC with integrated bio-impedance AFE enables ±1% impedance accuracy across 50Ω~1.5KΩ range, supporting multi-segment and multi-frequency analysis.

Ultra-Low Power Design

Sleep current <1.5μA, measurement current ~10mA. Supports 4×AAA batteries for 500+ measurements, ideal for smart scales.

🔧

Highly Integrated SoC

Built-in BIA AFE, excitation signal generator, weight sensor interface, LCD driver, and temperature sensor reduce external components by 35%.

📊

Advanced Body Composition Algorithms

Comprehensive algorithm library for body fat %, muscle mass, bone mass, BMI, BMR, visceral fat, and hydration level calculation.

🛡️

Multi-User Support

Extended memory supports 8+ user profiles with automatic user recognition based on weight and impedance patterns.

🔌

Smart Connectivity

Optional BLE/Wi-Fi connectivity for smartphone app integration, enabling trend tracking, goal setting, and cloud synchronization.

Recommended MCU Products

Select the optimal chip model based on your product requirements

BH66F2665

RECOMMENDED

Body Fat Measurement Flash MCU

📊 Key Specifications

VDD
2.2V~5.5V
Program Memory
16K×16
Data Memory
1024×8
Data EEPROM
1024×8
Package
QFN24 QFN32 LQFP48

Features

  • Low Power Consumption and Wide Operating Voltage
  • Highly Integrated Memory and Interfaces
  • Enhanced System Safety and Reliability
  • High-Precision Bia-Sensing Analog Front-End
View Datasheet →

Development Support & Resources

Comprehensive development resources to accelerate your time-to-market

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Need More Technical Support?

Our technical team is ready to provide professional consultation and customized solutions

Frequently Asked Questions

What body composition metrics can be measured?

Our solution supports comprehensive metrics including body fat %, muscle mass, bone mass, body water %, BMI, BMR, visceral fat level, and protein percentage.

What is the difference between single-frequency and multi-frequency BIA?

Single-frequency (50kHz) BIA is suitable for basic body composition analysis. Multi-frequency (5kHz~100kHz) BIA provides more accurate segmental analysis and can differentiate intracellular/extracellular water.

How many user profiles can be stored?

Our high-end MCU (BH67F2493) supports 8+ user profiles with automatic user recognition. The mid-range MCU (BH67F2476) supports 4 user profiles.

What is the typical measurement accuracy?

Impedance measurement accuracy is ±1% across 50Ω~1.5KΩ range. Body composition metrics accuracy depends on algorithm calibration, typically ±3-5% for body fat percentage.

Is smartphone connectivity supported?

Yes, our high-end MCU supports BLE/Wi-Fi connectivity for smartphone app integration, enabling trend tracking, goal setting, and cloud synchronization.

Can the solution support segmental BIA analysis?

Yes, our high-end MCU (BH67F2493) supports 8-electrode segmental BIA for separate analysis of arms, legs, and trunk.

Related Articles

Continue with articles covering adjacent engineering topics and implementation details.

Solution Evaluation

Body Composition Module Quick Selection - Product Fit, Accuracy Difference, and Integration

For product managers, buyers and engineering teams new to the BestHealth body composition solution, this article first answers four first-pass questions: which modules are available, what product each fits, how much accuracy differs between four-electrode and eight-electrode solutions, and how to integrate the module into the finished device. It then compares BMH05104-2, BMH05108 and BMH05109, and explains what makes a strong body composition solution: a self-designed BIA measurement front end, validation data, certification support, SDK/API completeness, structural design support and response speed.

June 26, 2026

Solution Evaluation

Validation Results - BestHealth Body Composition vs Hospital DEXA and Professional BIA Devices

For manufacturers evaluating the BestHealth BMH05104-2 / BMH05108 / BMH05109 body composition modules and looking for accuracy-validation data, this article publishes same-period comparison results from a 100-person cohort: against two tertiary-hospital DEXA references (the gold standard), muscle mass correlation is 0.978-0.983; against marketed professional BIA comparison devices, fat-free mass, skeletal muscle mass, fat mass and body-fat percentage correlate 0.978-0.995; dual-hospital DEXA cross-validation provides an additional reliability reference.

June 25, 2026

Engineering Debugging

How to Use Impedance Data to Troubleshoot BIA Body Composition Measurement

A BIA measurement debugging guide for the BMH05104-2 / BMH05108 / BMH05109 body composition modules, covering why to go back to raw impedance data, normal impedance magnitudes (the eight-electrode body model), a check order of stability then frequency relationship then segmental symmetry, and how to locate common faults in electrode contact, cable parasitic coupling, broken wires, and measurement posture.

June 15, 2026

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