Hole Matrix Mapping Model for Partitioned Sitting Surface Based on Human Body Pressure Distribution Matrix
Abstract
:1. Introduction
2. Experiment on Human Body Pressure Distribution of the Buttocks and Thighs While Sitting
2.1. Experimental Subject and Method
2.1.1. Experimental Apparatus and Parameter
2.1.2. Experimental Subjects
2.1.3. Experimental Procedure
2.1.4. Standardization
2.2. Statistical Analysis
2.2.1. Measurement Data Analysis
2.2.2. Analysis of Subjective Evaluation Results
2.3. Results and Analysis
2.3.1. Calculation of the Similarity of Body Pressure Distribution Maps
2.3.2. Human Body Pressure Distribution Maps for Top 10% Comfort Ranking
2.3.3. Human Body Pressure Distribution Indicators
3. Ideal Pressure Distribution Matrix and Zone Partition
3.1. Ideal Pressure Distribution of Sitting Posture
3.2. Ideal Pressure Distribution Matrix and Its Zones
4. Prototype Production of Ideal Pressure Distribution
4.1. Determination of Key Ergonomic Node Coordinates
4.2. Protype of Ideal Cushion
5. Experimental Study on the Model of Ideal Cushion Prototype
5.1. Experiment on Pressure Distribution of the Model of Ideal Cushion Prototype
5.2. Results and Analysis
5.2.1. Comparative Analysis of Data for Each Sex
5.2.2. Subjective Scoring Analysis
6. Conclusions
- (1)
- Through the analysis of the ideal pressure distribution map, the sitting contact surface can be divided into three zones: the ischial zone, the buttock zone, and the thigh zone. The ideal body pressure distribution index of each zone is shown in Table 4.
- (2)
- The similarity of the pressure distribution of a seat cushion to the ideal pressure distribution reflects comfort to some extent. The similarity of the pressure distribution matrices is compared with the subjective comfort scores. The two are highly consistent. Whether or not the ideal pressure distribution matrix can be reproduced more accurately is an important indicator for evaluating the comfort of the seat cushion.
- (3)
- The partitioned hole matrix mapping method can reproduce pressure distribution maps between different materials (e.g., mesh surface and memory foam). This method can be used to design memory foam chairs that perform competitively with existing mesh chairs and can be fabricated more easily for a lower cost. Therefore, this method is important for the design and development of ergonomic chairs.
7. Future Prospects
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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A | B | C | D | E | F | G | |
---|---|---|---|---|---|---|---|
Length (mm) | 500 | 500 | 600 | 600 | 500 | 600 | 500 |
Width (mm) | 400 | 400 | 450 | 450 | 400 | 450 | 400 |
Height (mm) | 60 | 50 | 60 | 60 | 50 | 50 | 70 |
material | Mesh fabric | Mesh fabric | Mesh fabric | Mesh fabric | Mesh fabric | Mesh fabric | Mesh fabric |
Name of the Target Muscle | Psoas | Gluteus Maximus |
---|---|---|
Electrode location |
Male | Male and Female |
---|---|
0.832 | 0.581 |
Male | ||||||||
---|---|---|---|---|---|---|---|---|
Upright Posture | Forward Sitting Position | |||||||
E/S7 | A/S5 | D/S7 | F/S6 | E/S7 | A/S5 | D/S7 | F/S6 | |
Comfort score | 27 | 25 | 24 | 24 | 27 | 25 | 24 | 24 |
Average pressure (Kpa) | 3.50 | 3.46 | 3.25 | 2.86 | 3.18 | 2.91 | 2.66 | 2.81 |
Peak pressure (Kpa) | 3.69 | 3.58 | 3.38 | 2.96 | 3.28 | 3.16 | 2.82 | 3.06 |
Maximum pressure gradient (Kpa/m2) | 1.67 | 0.98 | 1.13 | 1.07 | 1.02 | 0.90 | 1.00 | 0.95 |
Mean pressure gradient (Kpa/m2) | 1.08 | 0.95 | 1.15 | 1.01 | 1.01 | 0.85 | 0.97 | 0.88 |
Female | ||||||||
Upright Posture | Forward Sitting Position | |||||||
C/S1 | D/S3 | E/S3 | F/S2 | C/S1 | D/S3 | E/S3 | F/S2 | |
Comfort score | 29 | 28 | 28 | 27 | 29 | 28 | 28 | 27 |
Average pressure (Kpa) | 2.76 | 2.12 | 2.71 | 2.32 | 2.35 | 2.05 | 2.75 | 1.86 |
Peak pressure (Kpa) | 3.08 | 2.26 | 2.88 | 2.41 | 2.83 | 2.27 | 3.08 | 2.07 |
Maximum pressure gradient (Kpa/m2) | 1.05 | 0.95 | 0.90 | 1.10 | 1.01 | 0.85 | 0.95 | 0.79 |
Mean pressure gradient (Kpa/m2) | 0.97 | 0.90 | 0.87 | 1.80 | 0.85 | 0.77 | 0.87 | 0.73 |
Male | |||
---|---|---|---|
B | C | D | |
Average pressure | 0.54 | 5.05 | 2.02 |
Peak pressure | 2.36 | 10.13 | 5.21 |
Maximum pressure gradient | 1.81 | 3.88 | 2.70 |
Mean pressure gradient | 0.32 | 1.07 | 0.56 |
Female | |||
B | C | D | |
Average pressure | 0.26 | 2.99 | 1.90 |
Peak pressure | 0.89 | 7.61 | 4.63 |
Maximum pressure gradient | 0.70 | 2.97 | 2.39 |
Mean pressure gradient | 0.38 | 0.76 | 0.39 |
B | C | D |
---|---|---|
Sacral Triangle Diamond Unit | Buttock Units | Thigh Units |
Femoral biceps | ischial tuberosity | hip joint |
S1 | S2 | S3 | S4 | S5 | |
---|---|---|---|---|---|
D (mm) | 8 | 10 | 15 | 18 | 20 |
K | 0.414 | 0.214 | 0.166 | 0.159 | 0.152 |
B | C | D | |
---|---|---|---|
K (Calculated) | 0.27 | 0.15 | 0.19 |
K (Actual) | 0.25 | 0.14 | 0.21 |
Male | ||||||
---|---|---|---|---|---|---|
S1 | S2 | S3 | S4 | S5 | ||
Upright posture | prototype test | 10.49 | 13.02 | 11.18 | 12.80 | 13.74 |
reference sample | 12.20 | 14.69 | 11.42 | 14.25 | 16.21 | |
Forward sitting position | prototype test | 10.36 | 14.39 | 10.38 | 10.45 | 15.21 |
reference sample | 8.66 | 12.43 | 9.05 | 10.36 | 14.79 | |
Female | ||||||
S1 | S2 | S3 | S4 | S5 | ||
Upright posture | prototype test | 11.73 | 12.05 | 13.69 | 9.56 | 12.57 |
reference sample | 11.80 | 15.49 | 16.43 | 10.99 | 16.97 | |
Forward sitting position | prototype test | 11.64 | 13.11 | 11.68 | 10.23 | 13.06 |
reference sample | 9.27 | 9.65 | 10.94 | 7.58 | 13.78 |
Hardness | Packing | Support | Fit | Subjective Feeling | ||
---|---|---|---|---|---|---|
Reference samples | Upright posture | 1.012 | 1.020 | 0.842 | 1.152 | 0.526 |
Forward sitting position | 1.392 | 0.985 | 0.816 | 1.176 | 0.941 | |
Prototype tests | Upright posture | 1.125 | 1.188 | 0.875 | 1.021 | 0.648 |
Forward sitting position | 1.188 | 0.944 | 0.764 | 0.938 | 0.939 |
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Lu, C.; Chen, Z.; Li, Y.; Fu, X.; Tang, Y. Hole Matrix Mapping Model for Partitioned Sitting Surface Based on Human Body Pressure Distribution Matrix. Healthcare 2023, 11, 895. https://doi.org/10.3390/healthcare11060895
Lu C, Chen Z, Li Y, Fu X, Tang Y. Hole Matrix Mapping Model for Partitioned Sitting Surface Based on Human Body Pressure Distribution Matrix. Healthcare. 2023; 11(6):895. https://doi.org/10.3390/healthcare11060895
Chicago/Turabian StyleLu, Chunfu, Zeyi Chen, Yu Li, Xiaoyun Fu, and Yuxiao Tang. 2023. "Hole Matrix Mapping Model for Partitioned Sitting Surface Based on Human Body Pressure Distribution Matrix" Healthcare 11, no. 6: 895. https://doi.org/10.3390/healthcare11060895
APA StyleLu, C., Chen, Z., Li, Y., Fu, X., & Tang, Y. (2023). Hole Matrix Mapping Model for Partitioned Sitting Surface Based on Human Body Pressure Distribution Matrix. Healthcare, 11(6), 895. https://doi.org/10.3390/healthcare11060895