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J
ESK
J Ergon Soc Korea 2015; 34(3): 199-215
http://dx.doi.org/10.5143/JESK.2015.34.3.199
http://jesk.or.kr eISSN:2093-8462
Analysis of Human Body Suitability for Mattresses by
Using the Level of PsychoPhysiological Relaxation
and Development of Regression Model
Seung Nam Min1, Jung Yong Kim2, Dong Joon Kim2, Yong Duck Park2, Seoung Eun Kim2, Ho Sang Lee2
1
Department of Fire Safety Management, Shinsung University, Dangjin-si, 343-861
2
Department of Industrial and Management Engineering, Hanyang University, Ansan-si, 426-791
Correspondin
g
Author
Jung Yong Kim
Department of Industrial and
Management Engineering, Hanyang
University, Ansan-si, 426-791
Mobile : +82-10-5771-2059
Email : whatsdream@naver.com
Received : October 01, 2014
Revised : March 16, 2015
A
ccepted : March 26, 2015
Copyright@2015 by Ergonomics Society
of Korea. All right reserved.
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cc
This is an open-access article distributed
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ttribution Non-Commercial License (http://
creativecommons.org/licenses/by-nc/3.0/), which
permits unrestricted non-commercial use,
distribution, and reproduction in any medium,
provided the original work is properly cited.
Objective: The purpose of this study is to find the level of physical relaxation o
f
individual subject by monitoring psychophysiological biofeedback to different types
of mattresses. And, the study also aims to find a protocol to make a selection of the
best mattress based on the measured information.
Background: In Korea, there are an increasing number of people using western
style bed. However, they are often fastidious in choosing the right mattress fo
r
them. In fact, people use their past experience with their old mattress as well as
the spontaneous experience they encounter in a show room to finally decide to
buy a bed.
Method: Total five mattresses were tested in this study. After measuring the elasticit
y
of the mattresses, they were sorted into five different classes. Physiological and
psychological variables including Electromyography (EMG), heart rates (HR), oxygen
saturations (SaO2) were used. In addition, the peak body pressure concentration rate
was used to find uncomfortably pressured body part. Finally, the personal factors
and subjective satisfaction were also examined. A protocol was made to select the
best mattress for individual subject. The selection rule for the protocol considered
all the variables tested in this study.
Results: The result revealing psychological comfort range of 0.68 to 0.95, dermal
comfort range of 3.15 to 6.07, back muscle relaxation range of 0.25 to 1.64 and
personal habit range of 2.0 to 3.4 was drawn in this study. Also a regression model
was developed to predict biofeedback with the minimal use of biofeedback devices.
Moreover results from the proposed protocol with the regression equation and
subjective satisfaction were compared with each other for validation. Ten out of twent
y
subjects recorded the same level of relaxation, and eight subjects showed one-level
difference while two subjects showed two-levels difference.
Conclusion: The psychophysiological variables and suitability selection process used
in this study seem to be used for selecting and assessing ergonomic products
mechanically or emotionally.
Application: This regression model can be applied to the mattress industry to
estimate back muscle relaxation using dermal, psychophysiology and personal habit
values
Keywords: Mattress selection, Physical relaxation, Psychophysiological variables, Pea
k
body pressure
200 Seung Nam Min, et al. J Ergon Soc Korea
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1. Introduction
1.1 Background
Sleep is an important part relieving human body fatigue, and recovering the vitality of the following day in modern life. Because,
most people spend time equivalent to 1/3 of whole life in a bed, sleep in a comfortable bed is essential to health (Cooper et al.,
1980; Eden, 1961). Yang (2001) said growth hormone and anabolic hormones including prolactin, testosterone and progesterone
show sleep-related secretion rhythm, which supports the stamina recovery theory. Namely, he asserted that taking enough sleep
in a comfortable bed recovers day's physical and mental fatigue through physiological recharge process for cerebral restoration.
There are various factors affecting sleep. Although, there are essentially internal problems within human body, various external
factors are also related. Especially, Park (1995) said the most important thing to make sleep posture comfortable is the performance
of a bed. When sleep posture is imperfect, due to the use of a bed unsuitable for human body, the effect spreads to muscles
or each organ's hyper metabolism, and adds fatigue to human body, because no order is delivered to nervous system (Park,
2001). If the quality or quantity of sleep lacks, mental stress gets higher, as well as physical fatigue. If one does not take enough
sleep, the person reaches to self-dissolution, hallucination and oblivion (Donaldson and Kennaway, 1991).
Suckling et al. (1957) identified a hard mattress not only disturbs sleep, but makes a person not have deep sleep, and toss and
turn. Michael (2007) asserted more flexible mattresses relieve chronic pain, compared to than hard mattresses. Kanz and Gertis
(1964) said a pillow and a mattress are the factors regarded as important in the sleep environment. Parsons (1972) said the
mattress of a bed is good to have some degree of hardness.
Looking at preceding studies from an ergonomic aspect, the measurement of peak human body pressure distribution and
user's subjective questionnaire evaluation were used in the studies on mattresses (Parson, 1972). In particular, peak body pressure
distribution was described as one of the important variables (Bader and Engdal, 2000).
Kovacs et al. (2003) reported spinal part is not heavily bent or does not become gentle, only if peak body pressure is evenly
distributed on the main parts of human body (head, body, waist and leg). Lahm and Iaizzo (2002) observed that the discomfort of
back and waist muscles increases, if one does not maintain the straight shape of spine, when he/she lies down on a mattress.
Examining domestic study trend, studies were conducted, centered on physical characteristics and physiologic responses, such
as sleep environmental status (Shin, 1983; Na, 1989), bed instrument and human body response (Kim and Choi, 1991; Lee et al.,
2000). Recently, Kim et al. (2007) reported a mattress, in which the increase rate of skin temperature is low, increases subjective
comfort, although dermal pressure is equal in various mattresses. Yu et al. (2009) measured physical indices (EMG, heart rate,
oxygen saturation), psychological index (private property survey), peak body pressure and subjective satisfaction, and studied
the relevance between physical and psychological indices and subjective satisfaction. However, an assessment of user suitability
for a mattress, or an assessment method that can select a mattress is currently inadequate.
The purpose of this study is to identify whether psychopsysiological signals and peak body pressure occurring, when one lies
down on a mattress, can reveal body responses well. The purpose is also to develop a method selecting the most comfortable
mattress to human body and a mathematical prediction equation.
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2. Methods
2.1 Hypothesis and procedure
Yu et al. (2009) performed a mattress suitability analysis using EMG, HR, oxygen saturations, private property survey and
psychophysiological indices by measuring peak body pressure. As a result, they reported a comfortable mattress has significant
correlation with peak body pressure concentration rate, back muscle relaxation, heart rate (HR) and subjective satisfaction. This
study conducted an experiment with a study hypothesis that the mattress is likely to be a suitable one, if one's HR, EMG and
peak body concentration rate decreases, and oxygen saturations increase, when one lies down on the mattress. To this end,
this study measured the hardness of five mattresses with a hardness tester, and proposed a mathematical prediction equation,
based on the result (Figure 1).
2.2 Participants
In view of the characteristics of this study, 20 people aged 20~30 with good current health status and having no musculoskeletal
disorders related with back for the past one year were collected for the experiment. The subjects were instructed not to do
over-exercise and not to stay up all night before the experiment so that fatigue cannot be accumulated. The participants were
sufficiently explained on the details and purpose of the experiment before the experiment, and the subjects participated in the
experiment voluntarily, after filling out the experiment consent. All participants were males, and Table 1 shows anthropometric values.
Selecting mattresses - Classification of mattresses based on strength
Measuring psycho-physiological relaxation
- Measuring EMG, pressure, heart rate, and oxygen saturation
Data analysis
- Analyzing correlations between variables measured
Establishing methodology to select a mattress
- Establishing how to select a mattress through physical
Proposing mathematical equations
- Regression equation using Back muscle relaxation
Verifying final prediction equation
- Comparing estimated results of prediction equation with subjective satisfaction
Figure 1.
Flow-chart
Tabl e 1 .
Information on participants (
N
=20 male)
Age Height (cm) Weight (kg)
Mean 27.1 167.1 66.2
SD
±
6.4
±
7.2
±
18.4
202 Seung Nam Min, et al. J Ergon Soc Korea
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2.3 Design
The variables for the experiment consisted of psychophysiological variables (EMG, HR and oxygen saturations) and peak body
pressure. Private property (subject satisfaction) on each mattress was used for comparison with and verification of the results
selected by those variables (Table 2).
2.3.1 Private property survey
Before conducting the experiment, the participants were instructed to reveal their personal information, sleep posture and sleep
time, and to answer whether they used a mattress. To find out the participant's habit of using a mattress, this study carried out
a questionnaire survey. The questionnaire was designed to be divided into five items, and the experiment participants were to
answer with 5-point scale (Table 3). The private property survey was used by converting name type to value type, namely one
point for strongly disagree and two points for disagree. The questionnaire survey was conducted again, if a participant answered
"I like a hard mattress" on question No. 1, and then, "I like a soft mattress" on question No. 3, regarding the person as not
answering sincerely, through mutual verification on questions.
Tabl e 2 .
Independent variables used to measure the comfort of the mattress
Measured variables Definition
Electromyography: EMG Back muscle relaxation Decrement of muscle activity before and after using a mattress
Heart rate: HR Psychological comfort Decrement of heart rate before and after using a mattress
Oxygen saturation: SaO2 Cardiac efficiency Increment of oxygen saturation in peripheral vessels before and
after using a mattress
Peak body pressure: PBP Dermal comfort The ratio of peak pressure to mean pressure when lying on a
mattress
Tabl e 3 .
Questionnaire for likert score regarding personal experience and preference (example)
Strongly disagree
(1)
Disagree
(2)
Neither agree
nor disagree
(3)
Agree
(4)
Strongly agree
(5)
(1) I like a hard mattress. ν
(2) I have felt pain in the back while using
the mattress. ν
(3) I like a soft mattress. ν
(4) I feel pain on a certain part after using
the mattress. ν
(5) I have used or use a rather hard mattress. ν
30 Jun, 2015; 34(3): Analysis of Human Body Suitability for Mattresses 203
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2.3.2 Back muscle relaxation in EMG
For the back muscle relaxation measurement, electrodes were attached on the left and right of transverse abdominis between
L4 (lumbar vertebra 4) and L5 (lumbar vertebra 5) of the participants using EMG measurement equipment, and extracted data
for 60 seconds, respectively, when they stood and lied down on a mattress. To obtain stable signals from the extracted data,
this study calculated IEMG (integrated EMG) by extracting last ten seconds' signals (50~60 seconds). This study calculated back
muscle relaxation through Equation (1).
Back Muscle Relaxation i = IEMG i (lying50s~60s) /IEMGi (standing50s~60s) (i = 1, 2, 3, …, 20)
(1)
2.3.3 Psychological relaxation in HR
This study measured heart rate (HR) by installing a measurement equipment sensor on participant's index finger. This study
extracted data of 60 seconds, respectively, when a participant stood and lied down on a mattress, and calculated by extracting
the signals of last ten seconds (50~60 seconds) in order to obtain stable signals from the extracted data. This study calculated
psychological relaxation through Equation (2).
Psychological Comfort i = HRi (l ying50s~60s)/HRi(standing50s~60s) (i = 1, 2, 3, …, 20)
(2)
2.3.4 Whole body relaxation in SaO2
This study measured oxygen saturations (SaO2) by installing the measurement sensor on participant's index finger. This study
extracted the data of 60 seconds, respectively, when a participant stood and lied down on a mattress. This study calculated by
extracting the signals of the last 10 seconds (50~60 seconds) to obtain stable signals from the extracted data. This study
calculated whole body relaxation through Equation (3).
Cardiac Efficiency i = SaOi (lying50s~60s) /SaOi (standing50s~60s) (i = 1, 2, 3, …, 20)
(3)
2.3.5 Pressure concentration in PBP
This study measured peak body pressure (PBP) of the participants by installing a PBP gauge on a mattress. This study calculated
peak pressure concentration through Equation (4) by finding human body parts (head, back and hip), where peak body pressure
is generated.
Dermal Comfort i = (P1stmaxi+P2ndmaxi+P3rdmaxi)/Ptotal average (i = 1, 2, 3, …, 20)
(4)
2.4 Equipment
This study selected five types of mattresses with different spring shapes produced by S company in Korea. The size of the
mattresses was queen size, and the five types of mattresses were the same in dimensions: 1,700mm in width, 2,075mm in length
and 250mm in height. However, the hardness of springs the inside was different. To find out whether hardness differences existed
between the mattresses, each mattress' hardness value was measured, according to each mattress' pressed depth (0~80mm)
using S company-manufactured static load experimenting device. For measurement method, this study complied with ASTM
F1566-14. Consequently, the hardness of mattresses was significantly different (
p
<.01), and the post hoc test results revealed all
mattresses were significantly different in the mattress hardness (
p
<.01) (Table 4).
204 Seung Nam Min, et al. J Ergon Soc Korea
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This study also compared the strength of each mattress, which revealed statistically significant difference as such. As a result,
mattress three was revealed as the strongest mattress, followed by mattresses one, two, four and 5 in the order. This classification
was re-classified with a, b, c, d and e in the order of the mattress' strength. As shown in Figure 2, the lowest value of the first
grade mattress was 14.33, and it was classified into the most comfortable bed. The third grade mattress' average value was 31.44,
which was classified into the hardest bed.
To measure the participants' psychophysiological signals, this study used EMG, PBP distribution plate and HR (oxygen saturations)
equipment (Table 5).
Tabl e 4 .
Results of ANOVA on mattresses with different strength
Source Type III sum of squares df Mean square F
p
-value
Mattress 15463.161 4 3865.790 221.268 .000
Tabl e 5 .
Equipment applied
Name Model Made Picture
EMG ME-6000T Mega electronic (Finland)
Body pressure distribution plate SPDP Sigma system (Korea)
Figure 2.
Mattress grades as per strength
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2.5 Experiment process
This study measured anthropometric data of the participants, and a private property survey on mattress using habit and preference
was conducted before the experiment was carried out. This study also explained the experiment process to the participants,
attached each bio signal measurement equipment to each participant, and checked stable signals.
To improve data collection reliability, the onsite experimental conditions were defined as follows: The experiment was conducted
covering each mattress' brand to remove prejudice against mattress. The participants could not talk, during the experiment, and
they were instructed to participate in the experiment wearing the prepared pajamas, namely, the most comfortable outfit. The
experiment was undertaken at pleasant indoor temperature of 26℃ so that sleep could not be disturbed with too hot or too
cold temperature (Lee et al., 2000). In addition, the mood of night was created by turning off all the lights and pulling the curtain.
If a participant was judged to become sufficiently stable, after the person lied down on the mattress with medium level of strength
for about ten minutes, this study measured EMG, HR and oxygen saturations signals for one minute, when a participant stood.
The same method was used, when a participant lied down on the mattress to measure for one minute. In this experiment, PBP
distribution was measured, when a participant stood on the mattress to measure. After the measurement, Also, PBP distribution
was measured, when a participant lied down on the mattress to measure. After the measurement was finished, each participant
lied down on five different mattresses, and recorded subjective satisfaction with each mattress.
2.6 Analysis of body fitness assessment
To express private properties recorded with grade information per mattress, subjective satisfaction assessment results and the
quantitative information measured from psychological bio signals and PBP as unified mathematical result values, they were
converted to grade information. To decide physical relaxation and the suitability of mattress strength, this study applied the
following bio-mechanical principle. As shown in Figure 3, it is difficult to maintain spinal arch curve, because X and Y are formed
less, if the elasticity of a mattress is not enough in general. Therefore, ideal lumbar vertebral curvature angle can be maintained
by elasticity, as a mattress is harder. For this reason, it is good to recommend a hard mattress to a person without a problem
in physical relaxation required for sleep. However, a bit softer mattress is recommended to a person with relatively insufficient
back muscle or physical relaxation in order to complement demerits that may be caused by a hard mattress.
This study also verified the normalization of grade-information data through one-sample kolmogorov-smirnov test as shown in
Table 6 .
Tabl e 5 .
Equipment applied (Continued)
Name Model Made Picture
Physiological signals Pulse oximeter Nihon kohden (Japan)
206 Seung Nam Min, et al. J Ergon Soc Korea
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This study carried out normalization review on the variables revealing physical relaxation (peak body pressure concentration,
psychological relaxation, back muscle relaxation and whole body relaxation) and private property. If data does not follow normal
distribution, it is to minimize bias by grade that is caused, when grade is classified with a regular gap. As a result, oxygen saturations
values did not conform to normal distribution, and therefore, the values were excluded from the final psychophysiological variables.
3. Result
3.1 Results of personal habit survey
In the personal habit survey, maximum value 3.40 and minimum value 2.00 were revealed, and Figure 4 shows the comparative
result with mattress grades. Fifth grade was shown between 3.40~3.12, fourth grade between 3.12~2.84, third grade between
2.84~2.56, second grade between 2.56~2.28, and first grade between 2.28~2.00.
3.2 Result of back muscle relaxation in EMG
Judging that low EMG value means the use of a hard mattress can sufficiently relax back muscle, a logic that a hard mattress
favorable to spinal support can be used was used in this study. On the contrary, this study decided grade by mattress grade
corresponding to the judgement that a slightly soft mattress that can relax back muscle's tension is necessary, because high EMG
value means tensed back muscle under any circumstances. The measured values were maximum 1.64 to minimum 0.23, and a
comparison was made with mattress grades. The result was shown in Figure 4, and the fifth grade was between 0.23~0.51, fourth
grade between 0.51~0.79, third grade between 0.79~1.08, second grade between 1.08~1.36, and first grade between 1.36~1.64.
Tabl e 6 .
One-sample kolmogorov-smirnov normal distribution verification
Back muscle
relaxation
Psychological
comfort
Dermal
comfort
Personal
habit
Cardiac
efficiency
N 20 20 20 20 20
Kolmogorov-Smirnov's Z 0.422 0.722 0.694 0.909 1.790
Approximate significance probability (two-sided) 0.994 0.674 0.722 0.381 0.003
Normal distribution (Yes/No) Yes Yes Yes Yes No
Figure 3.
Bio-mechanical principle for selecting a right mattress
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3.3 Result of psychological relaxation in HR
Low psychological relaxation means it's the difference is huge between the standing posture and lying posture, and thus
physiological relaxation is regarded as good. A mattress with high strength has higher grade. On the contrary, psychological
relaxation is regarded as no good, if the difference is small between the standing posture and lying posture. A mattress low
strength has higher grade. The measured values were maximum 0.95 to minimum 0.68, and this study compared with the
mattress grades. Figure 4 shows the result, and the fifth grade was between 0.68~0.73, fourth grade between 0.73~0.79, third
grade between 0.79~0.84, second grade between 0.84~0.89, and first grade between 0.89~0.95.
3.4 Result of dermal comfort in PBP
Low peak body pressure concentration means peak body pressure is evenly distributed, and the specific part of a mattress is
not hard on specific body part. Therefore, a mattress with high strength has higher grade. On the contrary, if peak body pressure
concentration is high, a specific part of a mattress is hard on specific body part. Therefore, a mattress with low strength has higher
grade. Measured values were maximum 6.07 to minimum 3.15, and this study compared with mattress grades. The result was
shown in Figure 4, and the fifth grade was between 3.15~3.74, fourth grade between 3.74~4.32, third grade between 4.32~4.90,
second grade between 4.90~5.49 and first grade between 5.49~6.07.
3.5 Result of subjective satisfaction survey
As a result of each participant's subjective survey, 11 participants preferred medium strength mattress. Through this result, it is
estimated that rather too hard or soft mattress can be felt uncomfortable to the participants, since healthy people without back
disease participated in the experiment.
Figure 4.
Psycho-physiological variables and mattress grades
208 Seung Nam Min, et al. J Ergon Soc Korea
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3.6 How to use relaxation index
This study built indices recommending mattress strength suitable for users using EMG, PBP, personal habit and HR. According
to the experiment method presented above, EMG, PBP, personal habit and HR are measured, when a user stands and also lies
down. When a user's HR is 0.81, PBP is 4.02, back muscle relaxation is 0.99, and personal habit is 2.98, the final mattress strength
level is calculated by calculating the average of the indices (Figure 5).
3.7 Comparison of relaxation index and subjective satisfaction
This study compared subjective satisfaction results, as a result of mattress strength recommendation index. Consequently, ten
Figure 5.
Comparison between physical relaxation and mattress level (example)
Figure 6.
Comparison between physical relaxation and subjective satisfaction level
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participants matched among 20 participants, and the remaining ten participants showed the result deviating just one level
(Figure 6).
3.8 Mathematical prediction
The measurement equation calculated above is complicated to use. Because, measurement equipment is attached to skin to
measure back muscle relaxation, users may feel resistance, or some women may reject the measurement. In this regard, this study
explored mathematical prediction equations that can measure back muscle relaxation.
3.8.1 Correlation between back muscle relaxation and psychophysiological variables
To identify correlation between back muscle relaxation and each psychophysiological variable, this study calculated Spearman's
Rank Correlation Coefficient using the SPSS15. Consequently, back muscle relaxation and peak body pressure concentration
(rs= .581), psychological comfort and personal habit (rs=.520) had relatively higher correlation as shown in Table 7.
3.8.2 Regression process in multiple regression analysis
This study conducted a multiple regression analysis to analyze the relationship between back muscle relaxation, a dependent
variable, and three independent variables, namely, psychological comfort, peak body pressure concentration and personal habit.
To elevate discrimination of the regression equation, each independent variable's grade value was squared from one to four in
order to increase R
2
value, the coefficient of determination indicating what percentage of deviation of the dependent variable is
explained by the independent variables. This study calculated the regression equation with the highest R
2
(Table 8).
Tabl e 7 .
Correlation analysis with each variable. N: subject number, ( ): significant
N
Dermal
comfort
Psychological
comfort
Cardiac
efficiency
Personal
habit
Back muscle
relaxation
Dermal comfort 20 - (-) .653 (.061) 0.170 (.408) .260 (.483) .581 (.063)
Psychological comfort 20 .653 (.061) - (-) .110 (.574) .349 (.475) .580 (.051)
Cardiac efficiency 20 .170 (.408) .110 (.574) - (-) .377 (.687) .454 (.689)
Personal habit 20 .260 (.483) .349 (.475) 0.377 (.687) - (-) .520 (.061)
Back muscle relaxation 20 .581 (.063) .580 (.051) .454 (.689) .520 (.061) - (-)
Tabl e 8 .
Process to increase R
2
values (example)
Square Back muscle relaxation
Dermal comfort Psychological comfort Personal habit R
2
Adjusted R
2
Standard error of estimates
1 2 1 .389 0.237 1.236
2 2 1 .384 0.230 1.241
3 2 1 .377 0.222 1.248
210 Seung Nam Min, et al. J Ergon Soc Korea
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Looking at the model summary in Table 9, R
2
, the result of three inputted independent variables, namely, peak body pressure
concentration, psychological comfort and personal habit, was 0.512. It explains the deviation of the dependent variable, back
muscle relaxation, as 51.2%.
The multi regression equation on back muscle relaxation's coefficient of determination, R
2
=.512, was calculated as shown in
Equation (5) (Table 10).
Y (Back Muscle Relaxation) = 2.077+0.504x1(Dermal Comfort) - 0.003x2(Psychological Comfort) + 0.178x3(Persona lHabit)
(5)
Tabl e 9 .
Result for R
2
value
R
2
Adjusted R
2
Standard error of estimates
0.512 0.262 0.806
Tabl e 8 .
Process to increase R
2
values (example) (Continued)
Square Back muscle relaxation
Dermal comfort Psychological comfort Personal habit R
2
Adjusted R
2
Standard error of estimates
4 2 1 .372 0.215 1.253
1 4 1 .512 0.262 0.806
2 4 1 .401 0.251 1.224
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
1 1 4 .345 0.181 1.28
2 1 4 .342 0.177 1.283
3 4 4 .363 0.204 1.262
4 4 4 .353 0.191 1.272
Table 10.
Result for coefficients
Unstandardized coefficients Standardized coefficients t
p
-value
B
SE
Constant
2.077
1.172 1.772 0.1
Dermal comfort
0.504
0.184 0.560 2.741 0.017
Psychological comfort
-0.003
0.002 -0.335 -1.649 0.023
Personal habit
0.178
0.373 0.098 0.478 0.062
30 Jun, 2015; 34(3): Analysis of Human Body Suitability for Mattresses 211
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3.8.3 Comparison of the prediction estimation results and subjective satisfaction
This study calculated back muscle relaxation estimated through the regression equation. Figure 7 compares mattress grades through
estimated back muscle relaxation and subjective satisfaction level. As a result, the back muscle relaxation and subjective satisfaction
results of ten participants among 20 participants matched, and those of eight participants showed just one level difference.
Those of two participants showed difference within two levels.
4. Discussion
This study identified correlation among psychophysiological signals that are generated, when a person lies down, and analyzed
whether variables can be used as a quantitative tool in selecting an optimum mattress. Main characteristics of the correlation
analysis on each psychophysiological variable regarding the measurement variables used for developing logical methodology and
mathematical prediction equation are summarized below:
The correlation coefficient of back muscle relaxation and peak body pressure concentration was rs =0.581, which is similar to the
result of Kovacs et al. (2003); Vanderwee et al. (2005) Kovacs et al. (2003) insisting that comfort increases, and subjective satisfaction
increases, as no specific mattress part is hard on one's specific body part, when one lies down on a mattress.
The correlation coefficient between back muscle relaxation and psychological comfort was rs =0.580, and heart rate (HR) fell,
when one laid down on a mattress with good psychological relaxation. The result is similar to the result of the study of Bader
(2000) saying that HR falls, when one lies down on a comfortable mattress. Like the result of the study of Vanderwee et al.
(2005) asserting that HR falls, if stress is small, it is judged that back muscle relaxation affects stress.
Lee and Hong (2001) conducted a questionnaire survey on the cushion property of a mattress and pressure sensation on the
buttocks targeting people in their teens to 70s in a fact-finding survey on various phenomena upon using a bed. They presented
a mathematical prediction equation (R
2
=0.580) on total comfort. As a result, they reported the degree of supporting spine by the
Figure 7.
Estimate results using the estimation formula (of back muscle relaxation) and subjective satisfaction level compared
212 Seung Nam Min, et al. J Ergon Soc Korea
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mattress has an impact on comfort. In this study, the similar result was drawn by conducting comparative verification with subjective
satisfaction, according to comparing back muscle relaxation estimated through the regression equation and subjective satisfaction
level. Although, the quality of sleep is judged by using polysomnography (Lee and Park, 2006; Tsai and Liu, 2008), peak body
pressure (Nicol and Rusteberg, 1985; Peter and Avaliono, 1998), magnetoencephalography (Higashi et al., 2003), psychological
signals (Kim et al., 2011; Kim et al., 1997) and heart rate (Kim et al., 1999), according to mattress strength, these methods are
not easy to be used by industrial businesses. In addition, studies to present a model for industrial businesses to easily use are
inadequate. This study proposed a mathematical model equation using bio signals, and this model equation has meaning in that
it can discern wrong selection of a mattress unsuitable for oneself. However, Defloor (2000) said discomfort becomes different,
according to sleeping posture, and Bader (2000) said the strength of a mattress affects the quality of sleep. Kawabata and Tokura
(1995) asserted the effects on the ratio of deep sleep are different, according to bed type in a sleep experiment using a water bed
and a spring bed. Addison et al. (1986) insisted mattress surface functions as a cause of insomnia. Likewise, many external factors
affect the selection of a mattress. In this regard, various variables need to be considered to enhance the accuracy of mathematical
prediction equation in the future.
5. Conclusion
This study proposed the methodology to select a suitable mattress through physical relaxation or a regression equation. The
psychophysiological variables and suitability selection process used in this study seem to be used for selecting and assessing
ergonomic products mechanically or emotionally. These variables are considered to be used as objective variables to mechanically
and emotionally assess mattresses or relevant ergonomic products.
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Author listings
Seung Nam Min:
msnijn12@shinsung.ac.kr; msnijn12@hanmail.net
Highest degree:
PhD, Department of Industrial Engineering, Hanyang University
Position title:
Professor, Department of Fire safety management, Shinsung University
Areas of interest:
Industrial Ergonomics, Human Sensibility, Biomechanics, Human Vibration, Industrial Safety, Fire safety
Jung Yong Kim:
jungkim@hanyang.ac.kr
Highest degree:
PhD, Department of Industrial Engineering, the Ohio state University
Position title:
Professor, Department of Industrial and Management Engineering, Hanyang University
Areas of interest:
UX/UI, Biomechanics, Cognitive psychology
Dong-Joon Kim:
whatsdream@naver.com
Highest degree:
Bachelor
’
s degree, Department of Mechanical Engineering, Hanyang University
Position title:
MS leading to PhD course
’
s Student, Department of Industrial Management Engineering, Hanyang University
Areas of interest:
Biomechanics, Signal Processing, Safety
Yong Duck Park:
duck234515@gmail.com
Highest degree:
Bachelor's degree
Position title:
MS student, Research Scientist in Korea Research Institute Standards and Science
Areas of interest:
Emotional Engineering, Ergonomics
Seoung Eun Kim:
havocangel@naver.com
Highest degree:
Physical Education Ph.D
Position title:
Post doc, Ergomechanics Lab, Hanyang University
30 Jun, 2015; 34(3): Analysis of Human Body Suitability for Mattresses 215
http://jesk.or.kr
Areas of interest:
Sports Biomechanics
Ho Sang Lee:
lamplee@naver.com
Highest degree:
Master, Department of Industrial Engineering, Hanyang University
Position title:
Chief researcher, Korea Automotive Testing & Research Institute
Areas of interest:
Cognitive, Lighting Ergonomics
