Subject: Examine HFES Seat Specifications

Dear ANSI,

We’re reaching out to examine how relying on univariate analysis along with an outdated dataset from ANSI/HFES 100-2007 might impact accommodation percentages. Upon a perfoming the analysis of seat height adjustment, seat pan width, and seat depth (covered in sections 8.3.3.1, 8.3.3.2, and 8.3.3.3 respectively), we have determined that employing univariate analysis may result in inaccuracies in accommodation rates.For instance, when considering seat height alone, the combined accommodation rate stands at \(96\%\). However, factoring in seat height, seat pan width, and depth together, the combined accommodation percentage drops to \(90\%\). Moreover, using the updated dataset (ANSUR-II) indicates the need for a review of seat specifications, particularly focusing on seat width. Furthermore, we have observed disporotional accommodations between the male and female populations. For example, simultaneous accommodation (accounting for height, width, and depth collectively) caters to \(97\%\) of males, while only \(83\%\) of females are accommodated. This discrepancy prompts a closer look at the design considerations for both genders.

Background

The seat height adjustment, depth and width are calculated using ANSUR-I with some allowance for heel and clothing. In section \(8.3.3.1\), the seat height upper and lower bounds [380,560] mm are evaluated from the \(95^{th}\) percentile of male and the \(5^{th}\) percentile of the female popliteal height and plus \(25\) mm heel, respectively. The height adjustment is meant to accommodate the shortest and tallest population with shoes. In section \(8.3.3.2\),the maximum seat pan depth (430 mm) is evaluated from \(5^{th}\) percentile of the female buttock-popliteal length with less than \(10\) mm margin, this to ensure that the shortest population popliteal does not touch the edge of the seat pan when their back is rested on the backrest. In section \(8.3.3.3\), the minimum seat pan width (450 mm)is calculated from the \(95^{th}\) percentile of the female sitting hip breadth with \(70\) mm allowance for clothing and movement.

Proposed Amendments

Based on the analysis using ANSUR-II data, we recommend the following updates to the seat height adjustment, seat depth and seat pan width.

Justification

Firslty, The recommendations are based on the recognition that population dimensions have changed since 1988, the year when ANSUR-I data was gathered. As an alternative, we have used to ANSUR-II data, which is reflective of the year 2012. The boxplots provided below depict the small shifts in anthropometric measures’ ranges between these two datasets, but notably in hip breadth.

Secondly, the HFES standard employs a univariate approach, where each measurement is assessed by itself. However, the issue of seat standard measures inherently a multivariant problem as it involves both human length and width measurements. It is expected that the correlation between these two sets of measurements would be weak; individuals may exhibit considerable variation in stature relative to their hip breadth, and vice versa. As illustrated in Figure 3, the correlation between female popliteal height and seated hip breadth is approximately \(0.08\). Univariate analysis does not take into account the correlation between anthropometric measures, potentially resulting in a higher percentage of disaccommodation. Figure 3 further illustrates female accommodation , assuming univariate height bounds of \([380,560]\) mm and a minimum hip breadth of \(450\) mm according to the HFES standard. Those who do not fit within this range are highlighted in red. However, it is important to note that univariate analysis fails to address individuals who fall outside both criteria simultaneously, indicated by the darker red region.

The analysis extends to examining the relationships between popliteal height and buttock-popliteal length, as well as between buttock-popliteal length and hip breadth. A higher correlation implies a potentially lesser impact when incorporating the measure into the comprehensive multivariate analysis. Furthermore, we can illustrate which gender experiences greater influence from the inclusion of these design variables in the multivariate analysis. Figure 3 illustrates that females are more significantly affected by the lower bound of 380 mm, indicating that if the seat is adjusted to this minimum, their feet may still not fully reach the ground. Figures 3 and 5 collectively suggest that considering seat pan width will likely lead to a reduction in accommodation percentage for both males and females- further analysis later shows that female are more affected. Additionally, Figure 4 highlights that the inclusion of the depth variable has a more effect on females compared to males.

To calculate the accommodations using HFES recommnedations, we calculated the augmented human measures by adding a heel of \(25\) mm and clothing \(10\) mm. Then we evaluated the accommodated percentiles based on the HFES bounds for seat height, seat pan width, and seat depth mentioned earlier. The below section details the analysis.

#margins
heelm <- 25 #mm men heel
heelf <- 25 #mm women heel
clothing <- 10 #mm clothing clearance used in the standard for depth and width
f <-  length(A2f$stature) # number of females
m <- length(A2m$stature)#number of males

#augmented popliteal height (P+ heel)
A2f$augpoplitealheight <- A2f$poplitealheight + heelf
A2m$augpoplitealheight <- A2m$poplitealheight + heelm
#augmented buttock popliteal length (BP+ clothing)
A2f$augbuttockpopliteallength <- A2f$buttockpopliteallength + clothing
A2m$augbuttockpopliteallength <- A2m$buttockpopliteallength + clothing

#augmented sitting hip breadth (HBS + clothing)
A2f$aughipbreadthsitting <- A2f$hipbreadthsitting + clothing
A2m$aughipbreadthsitting <- A2m$hipbreadthsitting + clothing

#overlapped ranges: [min of the two max , max of the two mins]
overlap_pht <- overlap(A2f$augpoplitealheight,A2m$augpoplitealheight)
overlap_bplen <- overlap(A2f$augbuttockpopliteallength,A2m$augbuttockpopliteallength)
overlap_hpb <- overlap(A2f$aughipbreadthsitting,A2m$aughipbreadthsitting) 

#seat height range [38,56]cm including shoes clearance and corrections factors. 
accom_ht_f <- (sum(A2f$augpoplitealheight  >= 380 & A2f$augpoplitealheight <= 560)/f)*100 
accom_ht_m <-  (sum(A2m$augpoplitealheight  >= 380 & A2m$augpoplitealheight  <= 560)/m)*100
accom_ht_mf <- (accom_ht_m + accom_ht_f)/2 #combined

  
#seat depth (-,43]cm including 1 cm margin. 
accom_dp_f <- (sum(A2f$augbuttockpopliteallength >= 430)/f)*100
accom_dp_m <- (sum(A2m$augbuttockpopliteallength  >= 430)/m)*100
accom_dp_mf <- (accom_dp_m + accom_dp_f)/2 #combined

#seat width [45,-)cm including clothing clearance
accom_pn_f <- (sum(A2f$aughipbreadthsitting  <= 450)/f)*100
accom_pn_m <- (sum(A2m$aughipbreadthsitting  <= 450)/m)*100
accom_pn_mf <- (accom_pn_m + accom_pn_f)/2 #combined

#height and depth 
accom_htdp_f <- ((sum(A2f$augpoplitealheight >= 380 & A2f$augpoplitealheight <= 560 & A2f$augbuttockpopliteallength >= 430))/f)*100
accom_htdp_m <- ((sum(A2m$augpoplitealheight >= 380 & A2m$augpoplitealheight <= 560 & A2m$augbuttockpopliteallength >= 430))/m)*100
accom_htdp_mf <- (accom_htdp_m + accom_htdp_f)/2 #combined

#height and width 
accom_htpn_f <- ((sum(A2f$augpoplitealheight >= 380 & A2f$augpoplitealheight <= 560 & A2f$aughipbreadthsitting <= 450))/f)*100
accom_htpn_m <- ((sum(A2m$augpoplitealheight >= 380 & A2m$augpoplitealheight <= 560 & A2m$aughipbreadthsitting <= 450))/m)*100
accom_htpn_mf <- (accom_htpn_m + accom_htpn_f)/2 #combined

#depth and width 
accom_dppn_f <- ((sum(A2f$augbuttockpopliteallength >= 430 & A2f$aughipbreadthsitting <= 450))/f)*100
accom_dppn_m <- ((sum(A2m$augbuttockpopliteallength >= 430 & A2m$aughipbreadthsitting <= 450))/m)*100
accom_dppn_mf <-  (accom_dppn_m + accom_dppn_f)/2 #combined
                       

# height, depth and pan 
accom_htdppn_f <- ((sum(A2f$augpoplitealheight >= 380 & A2f$augpoplitealheight <= 560 & A2f$augbuttockpopliteallength >= 430 & A2f$aughipbreadthsitting <= 450))/f)*100
accom_htdppn_m <- ((sum(A2m$augpoplitealheight >= 380 & A2m$augpoplitealheight <= 560 & A2m$augbuttockpopliteallength >= 430 & A2m$aughipbreadthsitting <= 450))/m)*100
accom_htdppn_mf <- (accom_htdppn_m + accom_htdppn_f)/2 #combined
Table-1: ANSI/HFES Seat Accommodation Data
Design Variable(s) Men (%) Women (%) Combined (%)
Height 100 93 96
Depth 100 99 99
Width 97 90 94
Height & Depth 100 92 96
Height & Width 97 83 90
Depth and Width 97 89 93
Height, Depth, and Width 97 83 90

Conclusion

Based on the data presented in Table 1 and Figure 6, it’s evident that there exists a disproportionate accommodation, with women have lower accommodation rates compared to men in univariate, bivariate, and multivariate seat analyses. According to the current HFES specification, approximately 7% of women would find their feet dangling after adjusting the seat to the minimum height. This discrepancy becomes even more pronounced as additional design variables are incorporated into the multivariate analysis, eventually reaching a 14% difference between men and women when height, width, and depth are considered simultaneously.

In summary, we recommend utilizing updated datasets and applying multivariate analysis to ensure proportional accommodations for both genders. The figures below provide examples of recommended ranges achieved through multivariate analysis, aiming to accommodate at least \(95\%\) of both males and females.

Thank you for considering our recommendation.

Sincerely,

Aliaa Maar