Thin-film pressure sensor-based intelligent seat pressure sensing system: sitting posture pressure distribution

1. Measurement Plan
1.1 Experimental Equipment and Materials

1.2 Sensor Selection
Sensor Specifications

The RP-C30-ST thin-film pressure sensor is a resistive pressure sensor with a range of 20g ~ 20Kg. Its core features include:
• Response time: <1ms, fast response
• Operating temperature: -40°C ~ +85°C
• Thickness: 0.45mm, flexible, conforms to curved surfaces
• Durability: Over 1 million cycles (1Kg force flexible pressing)
Application Characteristics Analysis
• Adult body weight typically ranges from 50~100kg. In a seated posture, approximately 75% of the weight is transferred to the seat cushion (with the remainder borne by the thighs and back). This experiment uses a 9-sensor array to distribute the load, with a theoretical average force per sensor of ~75kg × 75% ÷ 9 = 6.25kg. However, actual sitting pressure is non-uniform, with the ischial tuberosity region as the core pressure zone, where peak pressure can reach 30%~40% of body weight.
• This experiment directly collects AD values from 9 channels via CMCU-05B to obtain seat cushion surface pressure distribution characteristics for subsequent posture recognition analysis.
• Scalability: For higher-weight testing scenarios, sensors with larger ranges or higher-density arrays can be selected.

1.3 Sensor Layout Design
Combined with human sitting pressure distribution characteristics, sensor positions are arranged according to target measurement areas. This experiment adopts two layout schemes, with emphasis below on Scheme 1: a 3×3 array (9 sensors) on the seat cushion plus 1 additional sensor on the backrest.

The seat cushion area uses 9 RP-C30-ST sensors arranged uniformly in a 3×3 grid, focusing on covering bilateral ischial tuberosities and surrounding core pressure-bearing soft tissue regions. This layout ensures precise core pressure data collection while optimizing sensor count for cost efficiency. If budget permits, higher-density arrays (composed of multiple single-point sensors) can be deployed.

One pressure sensor is installed on the seat backrest for pressure acquisition, paired with a single-channel acquisition board for independent backrest pressure data collection, enabling synchronized analysis of seat cushion and backrest pressures.

1.4 Acquisition System (CMCU-05B Collector + Wireless Transparent Transmission Module)

This experiment employs the CMCU-05B multi-channel thin-film pressure display with a wireless transmission module to relay data to a PC wirelessly.

The CMCU-05B is a 9-channel thin-film pressure sensor detector with a built-in screen and battery. It can display real-time pressure data and distribution curves for all 9 channels and can also connect to a computer for simultaneous data recording and storage.

Given the large number of sensors and complex wiring in seat testing, this solution includes an RS485 wireless transmission module for wireless data transfer between the collector and the host computer, while avoiding cable restrictions on the tester's movements. This module supports one-to-many wireless networking, making it highly practical for multi-test-point or multi-test-group scenarios.

1.5 Data Collection and Processing
Collection Process:
9 RP-C30-ST sensors (3×3 array)
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CMCU-05B multi-channel thin-film pressure collector (synchronous acquisition)
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Wireless transmission board (serial port → wireless transmission)
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Host computer software (real-time pressure cloud map + pressure curve display)

2. Experimental Procedure
This article focuses on the experimental process and data analysis of Solution 1. For a live demonstration of both solutions, you can jump to the Bilibili video:
https://www.bilibili.com/video/BV1mPJN6yEcP/?spm_id_from=333.1387.homepage.videocard.click

2.1 Pre-Experiment Preparation

1. Sensor Attachment: Fix the thin-film pressure sensors onto the seat cushion surface using double-sided tape or adhesive to ensure alignment with the target body parts during sitting and prevent displacement.
2. Wiring Connection: Connect the leads of the 9 sensors to the CH1–CH9 terminals of the CMCU-05B collector board (sensor pins are non-polarized).
3. Connect the wireless transmission receiver board to the computer via USB;
4. Device Setup: Power on and pair the devices to confirm normal wireless communication.

2.2 Experimental Procedure
Experiment 1: Empty seat state. Record data from all 9 channels; no valid pressure signals should be detected from any sensor.

Experiment 2: Upright sitting posture. Sit in a standard upright position (back straight, legs naturally shoulder-width apart) and record 9-channel data.

Data Analysis:
• Key Features:

• Highest pressure values in the left and right ischial regions, with near symmetry
• Pressure at the front edge of the cushion is significantly lower than in the ischial regions (difference >50%)
• No backrest pressure • Conclusion: In a normal sitting posture, pressure is primarily concentrated in the ischial regions, with auxiliary support from the thighs. Pressure on the front thighs and cushion edge is minimal.

Experiment 3: Forward-leaning posture, lean the body forward (simulating desk work) and record 9-channel data.

Data Analysis:
• Key Features:

• Reduced pressure in the ischial regions (due to forward weight shift)
• Increased pressure in the thigh regions
• Significant rise in pressure at the front edge of the cushion
• No backrest pressure • Health Tip: Prolonged forward-leaning posture increases pressure on the front of the thighs and the popliteal fossa, affecting blood circulation in the lower limbs. • Conclusion: The forward-leaning posture changes the pressure distribution, and increased pressure on the front edge of the cushion is the main cause of leg discomfort.

Experiment 4: Leaning-back posture, leaning backwards (supported by the backrest, simulating a resting state), recording 9-channel data.

Data Analysis:
• Key Features:

• Peak pressure in the ischial area decreases (weight is distributed to the thighs and backrest)
• Pressure on the front edge of the cushion is close to zero
• Backrest pressure is present • Conclusion: Leaning-back posture reduces cushion pressure, with the backrest bearing part of the load, typically resulting in greater hip comfort.

3. Application Scenarios
3.1 Office/Automotive Driving Seat Health Monitoring
Lumbar spine problems and pressure ulcer risks caused by prolonged sitting are common health concerns.

Innovation Point: Multiple studies have shown that using pressure distribution sensing combined with active pressure redistribution can effectively reduce the risk of pressure ulcers.

3.2 Seat Product R&D and Testing

Professional pressure distribution testing systems have been widely used in the field of seat R&D. This solution achieves similar functionality at an extremely low cost.

4. Application Fields

5. Application Prospects
5.1 Technology Trends

1. Integration of Healthcare • Smart Pressure Ulcer Prevention Cushion: Research indicates that modular pressure redistribution systems can effectively prevent pressure ulcers • Remote Rehabilitation Monitoring: Sitting posture data is uploaded to the cloud for remote assessment by therapists • Elderly Care: Automatic alerts for prolonged sitting / abnormal postures
2. Data-Driven Product Iteration Seat manufacturers can optimize seat design parameters by collecting massive amounts of sitting posture pressure data, enabling data-driven product iteration.

5.2 Expansion Directions

5.3 Comparison with Professional Systems

Market Positioning: This solution does not seek direct competition with professional systems but instead provides an embedded sitting posture sensing solution that can be deployed at scale, filling the gap in the low-cost smart seat market.

6. Summary
This system uses nine RP-C30-ST thin-film pressure sensors (20kg range), arranged in a 3×3 array on the seat cushion. Real-time data acquisition and transmission are achieved via the CMCU-05B multi-channel thin-film pressure display and the RS485 wireless transparent transmission module.

Core Applications:
• Sitting posture monitoring and health reminders for office/driving seats
• Pressure ulcer prevention and posture monitoring in medical rehabilitation
• Comfort quantification testing in seat product development

In the context of the growing trend of smart seating, this solution provides a feasible technical path for deploying sitting posture sensing capabilities at scale, characterized by extremely low cost, low power consumption, and ease of integration, offering clear commercial value and social significance.

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