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ARTICLE IN PRESS
Journal of Biomechanics 43 (2010) 1667–1673
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Journal of Biomechanics
0021-92
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Unite d
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peyron@
www.JBiomech.com
Development and validation of a mastication simulator
A. Woda a,b, A. Mishellany-Dutour a,c, L. Batier d, O. Franc-ois a, J-P. Meunier c, B. Reynaud e,M. Alric c, M-A. Peyron f,n
a Clermont Universite, Universite d’Auvergne, EA 3847, Deficiences incapacites et desavantages en sante orale, BP 10448, F-63000 Clermont-Ferrand, Franceb CHU Clermont-Ferrand, Service d’Odontologie, F-63001, Clermont-Ferrand, Francec Clermont Universite, Universite d’Auvergne, ERT 18, Conception ingenierie et developpement de l’aliment et du medicament, BP 10448, F-63000 Clermont-Ferrand, Franced Poly’Tech, avenue des Landais, F-63170 Aubi�ere, Francee Nestle Research Center, PO Box 44, CH-1000 Lausanne 26, Switzerlandf INRA, UMR 1019, UNH, CRNH Auvergne, F-63000 Clermont-Ferrand, France; Clermont Universite, Universite d’Auvergne, Unite de Nutrition Humaine, BP 10448, F-63000
Clermont-Ferrand, France
a r t i c l e i n f o
Article history:
Accepted 4 March 2010More and more research are being done on food bolus formation during mastication. However, the
process of bolus formation in the mouth is difficult to observe. A mastication simulator, the Artificial
Keywords:
Mastication
Simulator
Food bolus
Chewing
Engineering
90/$ - see front matter & 2010 Elsevier Ltd. A
016/j.jbiomech.2010.03.002
esponding author at: INRA Institut National d
e Nutrition Humaine, 63122 Saint-Gen �es-Cha
3 04 73 17 73 84; fax: +33 04 73 17 73 88.
ail addresses: marie-agnes.peyron@clermont.i
clermont.inra.fr (M.-A. Peyron).
a b s t r a c t
Masticatory Advanced Machine (AM2) was developed to overcome this difficulty and is described here.
Different variables can be set such as the number of masticatory cycles, the amplitude of the
mechanical movements simulating the vertical and lateral movements of the human lower jaw, the
masticatory force, the temperature of the mastication chamber and the injection and the composition of
saliva. The median sizes of the particles collected from the food boluses made by the AM2 were
compared with those of human boluses obtained with peanuts and carrots as test foods. Our results
showed that AM2 mimicked human masticatory behavior, producing a food bolus with similar
granulometric characteristics.
& 2010 Elsevier Ltd. All rights reserved.
1. Introduction
Mastication transforms a food into a bolus suitable forswallowing (Lillford, 1991; Prinz and Lucas, 1995; Woda et al.,2006). Mastication also forms the first step in the digestionprocess. Direct evidence is lacking, but there are some clues thatpoor mastication is linked to poor nutrition and poor generalhealth (Morais et al., 2003; Ngom and Woda, 2002; Sheiham et al.,2001). Despite its importance, the process of bolus formation isunder-researched. For example, the physical and chemicalproperties of food change as it is transformed into a bolus, andthe mass exchange during mastication are unknown.
Studying the food bolus is hampered by the mere fact that itsformation occurs inside the mouth. A few artificial mouthssimulating mastication have been developed. Only one of these(Salles et al., 2007) allows the control and setting of some of themasticatory variables described in the literature (Peyron et al.,2002; Woda et al., 2006). Another one allows several variables tobe replicated, but only for the first bite (Meullenet and
ll rights reserved.
e la Recherche Agronomique,
mpanelle, France.
nra.fr,
Gandhapuneni, 2006). Most of the existing prototypes usecompressive forces with teeth that have anatomical shapes.However, the complex shapes of natural teeth are operantbecause of the action of the peripheral and central nervoussystems involving sophisticated feedback loops based on theperiodontal, muscular and mucosal receptors that control muscleactivities. In most machines only one functional variable, e.g.,speed, deformation or piston movement, can be controlled at atime. This is so for the texturometers of General Foods (Friedmanet al., 1963) and INRA (Sale et al., 1984) and other tools (Olthoffet al., 1984; Wang and Stohler, 1990; Slagter et al., 1992; Peyronet al., 1994; Heintze and Cavalleri, 2006). Many devices aredesigned to measure the flavour release from foods duringchewing (Nassl et al., 1995; Van Ruth et al., 1995). Othersoriented towards mechanical properties make no attempt toreproduce the conditions in which foods are prepared within aclosed mouth (Hoebler et al., 2002; Usui et al., 2003; Conservaet al., 2008). Mathematical models have also been proposed (Katoet al., 1988; Peleg and Normand, 1982; Van der Bilt et al., 1992;Daumas et al., 2005; Pap et al., 2005).
A new simulator, the Artificial Masticatory Advanced Machine(AM2) has been developed.1 Its purpose was to simulate the result
1 License 0706519 – 2007/17/09; http://masticateur.u-clermont1.fr/.
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A. Woda et al. / Journal of Biomechanics 43 (2010) 1667–16731668
of mastication, i.e. to produce a food bolus with properties similarto those produced by natural mastication, and not to duplicate theanatomical features of the teeth and mouth. However, the basickinetic characteristics of jaw movement were mimicked.
The pre-swallow bolus is characterised by a specific particlesize distribution that is similar across individuals (Lucas and Luke,1986; Peyron et al., 2004; Mishellany et al., 2006; Jalabert-Malboset al., 2007). This narrow variability may be explained by the vitalneed to reach a required pre-swallow bolus state because of thedanger of swallowing an unprepared bolus (Anderson, 1977). Theimportance of obtaining an adequate particle size explains whygranulometry has to date been by far the most frequently usedmeasure of bolus conformity although the rheological propertiesare also important (Coster and Schwartz, 1987). Normal mastica-tion was recently described using an indicator based on the pre-swallow bolus particle size (Woda et al., 2010). Accordingly, inthis study a calibration–validation procedure was based oncomparison between the particle size values of food bolusesobtained in subjects with good masticatory apparatus and thoseobtained with the AM2.
2. Materials and methods
2.1. Biomechanical principles for reproduction of human jaw movements and
teeth action
Jaw movement properties have been extensively analysed (Koolstra et al.,
1988;Gallo et al., 1997). The purpose of our project was not to reproduce the
continuously changing three-dimensional movements during mastication, but
rather the action of teeth on food. Thus to simulate basic jaw kinematics, we
focused on a simple kinetic model (Salaorni and Palla, 1994). We combined a
translational and a rotational movement in the machine, since they co-occur in the
mouth (Posselt, 1952).
Movement of the lower jaw during human mastication can be described as a
repetition of many cycles (�10–60), each stroke being composed of a vertical
opening and a vertical closing movement causing food compression between teeth.
Fig. 1. General view of the AM2 with the opened mastication chamber represented up
chamber are formed by the stationary ‘‘maxillary disk’’ (14) and the moving ‘‘mandibula
the central axis of the cylinder. 1: Frame. 2: Mastication chamber. 3: Fixed jaw sea
5: Mastication chamber plug for food introduction. 6: Heater regulating the inside t
Translation ball screw spindle. 11: Translation motor. 12: Rotation motor. 13: Moving
Simultaneously the jaw makes a lateral movement, which applies a shear stress to
the food. In the AM2, the vertical and lateral movements are obtained by translation
and rotation of a piston actuated by two computer-controlled motors (Fig. 1).
Fully functional dental arches are mostly observed in anthropological studies
in individuals from non-Western societies who display markedly worn teeth
(Kaidonis, 2008) with flattened chewing surfaces. In these subjects, chewing is
performed by confronting upper and lower flat occlusal surfaces. During the
occlusion, the lower molars slide against the upper molars through continuous
movement mostly directed forward and inward (Woda et al., 1979; Morel et al.,
1991). We thus did not take into account the shape of natural teeth, but only the
continuous chewing surface made, in each hemi-arch, by the five cheek teeth.
2.2. Description and functioning of the apparatus
In the human mouth, food undergoes shearing and compressive forces
between the opposing tooth arcades (Strait, 1997). The food particles are gathered
up by accurate, synchronised movements of the tongue, cheeks and lips. In the
AM2, these two actions are performed by two identically shaped surfaces (Fig. 2A)
whose active masticatory surface area is similar to the summed masticatory
surface areas of three contiguous premolar and molar teeth (170 mm2). During
continuous rotation, the surfaces of the mandibular disk meet the maxillary disk in
the three different positions (Fig. 2B to D). In position B, each active masticatory
surface meets the base of the opposing disk, applying compressive forces. In
position C, the active surfaces of the mandibular disk meet the active surfaces of
the maxillary disk, the bevelled edge of the masticatory surfaces sliding over their
opposing counterparts. When the mandibular disk meets the maxillary disk, it
applies a force on it, pressing it back against the spring fitted behind it. Thus the
force generated during the stroke depends on the stiffness of the spring. The
amplitude of the retraction of the maxillary disk is equal to the height of the active
masticatory surfaces. In this position, shear forces are applied that depend on the
strength of the spring, which can be varied by changing the spring. In position 2D,
the active masticatory surfaces are opposed and the spring is maximally
compressed. Every tooth stroke travels through positions B, C and D on the way
up, and then C and B again on the way back down. Position B allows the gathering
and transport of food particles towards the active masticatory surfaces where they
are crushed. In position B, there is a gap between the two disk bases, which
corresponds to the maximal void volume of the mouth (�15 cm3) during chewing.
A general view of the AM2 is given in Fig. 1. Three operating modes can be
selected. In the continuous mode, the number of tooth strokes/minute depends on
the uniform rotation speed. In the alternate mode, the rotation of the disk stops after
each stroke and an optic sensor re-sets the disk to position A (Fig. 2). In this mode
per left. The masticatory chamber (2) is a cylindrical cavity. The two ends of the
r disk’’ (13). The mandibular disk can move back and forth along and rotate around
t from which the bolus is extracted after opening. 4: Fixed jaw locking clamp.
emperature. 7: Saliva injection port. 8: Transmission shaft. 9: Force sensor. 10:
mandibular disk. 14: Stationary maxillary disk.
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A. Woda et al. / Journal of Biomechanics 43 (2010) 1667–1673 1669
the mandibular masticatory surface slides over the maxillary masticatory surface
only once per stroke (positions B and C). In the pressure mode the mandibular disk
acts by pressing against the maxillary jaw through a purely translational movement.
Electronics and a computer program control the many variables that enable
eaters to adjust their mastication to food properties. The main variables that may
influence the masticatory process are: number of strokes, duration of the
masticatory sequence from food intake to swallowing, amplitude of the masticatory
force, amplitude of the opening movement of the lower jaw, amplitude of the lateral
movement of the lower jaw and stroke frequency during the masticatory sequence.
Temperature and saliva production are also factors that can be simulated in the
artificial oral cavity. Artificial saliva (Hutteau and Mathlouthi, 1998; Van Ruth et al.,
1995) is injected through an opening (7 in Fig. 1) placed away from the masticatory
space, in a small spurt (about 0.05 ml) when the mandibular disk is in its most
retracted position during the stroke. The values of saliva flow range from 0.5 to
5 ml/min (Ben-Aryeh et al., 1986). The control of the AM2, performed in a closed
feedback loop design, is shown schematically in Fig. 3.
2.3. In vivo experiment
Young male (n¼15) and female (n¼15) subjects were recruited (22–29 years).
The inclusion criteria were: healthy complete dentition except for third molars,
normal maxillo-mandibular relationship, no previous orthodontic treatment, no
pharmacological drug liable to modify salivary secretion, no allergy to the
System links:
Computer Logic controller : Ethernet connexion . AM2 driving : parameters transComputer Force sensor : Analog acquisition .Logic controller Translation drive : Motor driving (closed loop ) « axis commandLogic controller Translation drive : serial link RS 232 (drive supervising ).Logic controller Rotation drive : Motor driving (closed loop) « axis command ».Logic controller Rotation drive : serial link RS 232 (drive supervising ).Logic controller Pump control unit : serial link RS 232 – pump driving .Logic controller Temperature controller : Serial link RS 232. Temperature contro
Analog acquisition
Ethernet connexion
PCDigital I/O
Serial ports server
RS-232
RS-232
Fig. 3. Schematic representat
Fig. 2. Maxillary and mandibular disks shown in the differe
test-foods, no pain in the area (temporo-mandibular joint and masticatory
muscles), no bruxism and no removable dentures. Crowns, bridges and other
fixed restorations were accepted when limited.
Portions were five nuts (3.5 g) and samples of raw carrots (height 1 cm,
diameter 2 cm, 4 g). There were three sessions. Session 1 was used for training,
during which the subjects chewed eight samples of each food. The first two
samples were swallowed to train the subjects to feel the time for a normal
swallow. The six other samples were used to train them to expectorate when the
swallowing time was reached. In session 2, the subjects also chewed eight samples
of each food, but the last two boluses of each food were kept for particle size
analysis. For the two swallowed samples, the experimenter counted the number of
masticatory cycles. The masticatory sequence ended when the subjects raised
their hand to signal they were ready to expectorate. The number of cycles obtained
during these two sequences was averaged and considered as the mean value until
swallowing. In session 3, the subjects were asked to deliver two boluses for
particle size analysis, one expectorated after 20 cycles and the other after 10
cycles. This protocol complies with the Declaration of Helsinki. It was approved by
the local Ethics Committee, and the subjects gave their informed written consent.
2.4. Particle size determination
The in vivo and in vitro boluses were characterized by their d50, the theoretical
sieve through which 50% of the particle weight could pass (Van der Bilt et al.,
fer & driving.
».
ller driving .
Drive Translation
Drive Rotation
Axis
com
man
d
Dig
italI
/O
CPJForce sensor
Dig
italI
/O
S-HDPump control
unit
RS
-232
Dig
italI
/O
Temperature controller
RS
-232
Dig
italI
/O
Programmable Logic Controller
Axi
sco
mm
and
Dig
italI
/O
ion of the AM2 controls.
nt positions during operation (see explanation in text).
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A. Woda et al. / Journal of Biomechanics 43 (2010) 1667–16731670
1993; Ngom et al., 2007). Expectorated and in vitro boluses were rinsed through a
100 mm sieve in running water and placed in an incubator (UFE 400–800,
Memmert, Germany) at 37 1C for 1 h (carrots) or 2 h (peanuts). The dried particles
were spread on a transparent plastic sheet and a scan shot taken (Epson Perfection,
4990 Photo). Computerized image analysis (Powdershapes, Innovative Sintering
Technologies, Ltd., Switzerland) then yielded the d50 of the particle size
distribution.
0
1
2
3
4
5
02selcyc01ovivniovivni 8.31 2.81
p
30
10 3
30
0
1
2
3
4
5
6
7
8
9
10
cyc02selcyc01ovivniovivni 2.812.81 5.32 52
3010
22 30
2
0
1
2
3
4
5
peanuts 26 cycles carrohtiwhtiw tuohtiw
10 10
10
0
1
2
3
4
5
02selcyc01ovivniovivni 8.31 2.81
p
d50
(mm
) 30
10 3
30
0
1
2
3
4
5
6
7
8
9
10
cyc02selcyc01ovivniovivni 2.812.81 5.32 52
3010
22 30
2
d50
(mm
)d5
0 (m
m)
0
1
2
3
4
5
peanuts 26 cycles carrohtiwhtiw tuohtiw
10 10
10
Fig. 4. Median particle sizes (d50) measured in vivo and in vitro (with different springs)
(A) and carrots (B). Black bars indicate the mean value obtained in vivo and the closest m
and temperature control’’ condition (C) were obtained using the 18.2 and 25 N/mm sp
2.5. In vitro experiment
For the in vitro experiment with the AM2, the variables of the AM2 took into
account a pilot study result indicating that number of cycles and stiffness of the
springs were the two main variables modifying the d50 of the boluses. Variations
in the d50 induced by different values of spring stiffness (variation of the forces)
were observed at three different stages during the chewing process (10 cycles, 20
selcyc62selcycovivni 8.318.31 2.812.81
eanuts
103
60 103
selcyc33selovivni
carrots
2.81 5.325.32 2.535252
10 260
102
2
4
ts 33 cyclestuohtiw
10
selcyc62selcycovivni 8.318.31 2.812.81
eanuts
103
60 103
selcyc33selovivni
carrots
2.81 5.325.32 2.535252
10 260
102
2
4
ts 33 cyclestuohtiw
10
at 10 cycles, 20 cycles and at the moment of swallowing for food boluses of peanuts
ean value obtained in vitro (see Table 2). Data recorded for with or without ‘‘saliva
rings for peanuts and carrots, respectively.
ARTICLE IN PRESS
Table 2Median particle size (d50) observed in vivo and in vitro at 10 cycles, 20 cycles and
at deglutition time for food boluses of peanuts and carrots. The in vitro values were
obtained with springs of ranging stiffness (N/mm: force developed per unit
compression distance). The spring values used in C for peanuts and carrots were
18.2 and 25.0 N/mm, respectively. The in vitro d50 values closest to the in vivo d50
are indicated in bold. This indicated the spring that had to be chosen to reproduce
the bolus particle size. n: number of repeats.
Number of cycles Spring STRENGTH (N/mm) d50 mean SD n
A Peanuts
10 cycles In vivo 2.49 0.58 30
13.8 2.34 0.23 10
18.2 2.00 0.52 3
20 cycles In vivo 1.39 0.17 30
13.8 1.66 0.25 3
18.2 1.36 0.12 10
26 cycles In vivo 1.39 0.19 60
13.8 1.36 0.15 3
18.2 1.38 0.11 10
A. Woda et al. / Journal of Biomechanics 43 (2010) 1667–1673 1671
cycles and swallowing, i.e. 26 for peanuts and 33 for carrots in reference to the
mean in vivo values). Temperature was set to room temperature, and 1.5 ml of tap
water was added before the beginning of the masticatory sequence. In other trials,
(Fig. 4C), the d50 values obtained with an artificial saliva at 37 1C were compared
with those obtained with tap water and at room temperature. Table 1 indicates the
values other than number of cycles and spring stiffness chosen to program
the AM2.
2.6. AM2 calibration–validation and statistical analyses
The calibration–validation was based on comparison between the in vivo and
in vitro values. Analyses were performed using SPSS software (v.14Windows, SPSS
Inc., USA). A three-way-ANOVA was performed with the three factors: type of food,
in vivo–in vitro and number of cycles. A two-way-ANOVA was then computed with
the two factors: temperature-saliva and food. In both cases, Student tests were
carried out for each food to compare the in vivo and in vitro values. To test the
reliability of the apparatus, a three-way-ANOVA was computed with the three
factors: repetition, type of food and number of cycles. Values were given as
mean7standard deviation (SD) and Po5% was chosen.
Number of cycles Spring strength (N/mm) d50 mean SD nB Carrots
10 cycles In vivo 6.74 1.34 30
18.2 6.49 0.91 10
23.5 5.55 0.35 2
25.0 4.60 0.56 2
20 cycles In vivo 3.88 0.96 30
18.2 4.30 0.14 2
23.5 3.67 0.38 10
25.0 3.55 0.21 2
33 cycles In vivo 2.78 0.60 60
18.2 3.30 0.28 4
23.5 2.55 0.07 2
25.0 2.73 0.30 10
35.2 2.10 0.00 2
Food & number of cycles Sal. temp d50 mean SD nC Saliva & Temperature
Peanuts 26 cycles with 1.24 0.08 10
Peanuts 26 cycles without 1.38 0.11 10
Carrots 33 cycles with 2.51 0.14 10
Carrots 33 cycles without 2.73 0.30 10
3. Results
The d50 values obtained from the particle size distributions forboluses collected in vivo at three times during the chewingprocess (10, 20 cycles and swallowing) are displayed in Fig. 4. Thenumber of masticatory cycles at swallowing was 2677.8 forpeanuts and 33711.05 for carrots. A significant decrease in thed50 along the three boluses collection times was observed exceptfor peanuts between 20 and 26 cycles. No significant differencebetween the repeats corresponding to the two boluses collectedfrom each subject was observed.
The calibration–validation was in two steps: calibration andcomparisons between in vitro and in vivo boluses. To calibrate theAM2, we determined the correct spring to be used by comparingthe mean d50 found with different springs with the in vivo d50.
This was done after 10 cycles, 20 cycles and at swallowing(26 cycles for peanuts, 33 for carrots). Two, three, four or tenboluses were obtained (Table 2). Table 2A and B shows the meanvalues of d50. Two springs were tested for peanuts. For carrots,three springs were tested when boluses were obtained after tenand twenty cycles and four springs were tested when boluseswere collected at swallowing. Ten boluses were obtained for eachof the chosen springs (best approximation to the in vivo valuesshown in bold in Table 2 and in black in Fig. 4). The second stepwas performed with these chosen springs by comparing in vivo
and in vitro values. This was done using the d50 obtained in the 60boluses (30 subjects) with the d50 obtained with the AM2 at thethree mastication times and for two foods. There was no effect ofthe in vitro/in vivo factor; a significant effect (Po0.001) was noted
Table 1Values of in vitro variables chosen for AM2 programming for peanuts and carrots
at three different times during the chewing process: 10 and 20 cycles for both
foods and 26 and 33 cycles for peanuts and carrots, respectively.
Food tests variables Peanuts–carrots
Function type Alternate
Temperature control temperature set point(degree C)
Off or on room or 371
Saliva controlSaliva modeVolume (ml)
On mono-injection 1.5
Cycle number 10, 20 and 26 or 33
Start angle (degree) 20
Stop angle (degree) 270
Retract length (mm) 20
Translation speed (mm/s) 100
Rotation speed (degree/s) 140
Sample rate (Hz) 200
for both food and number of cycles [three-way ANOVA,F(1.288)¼1.1;P¼0.29]. No interaction was noted between thein vivo–in vitro factor and either food or number of cycles. Nosignificant difference between in vitro and in vivo values was foundfor any of the six corresponding Student tests (0.26oPo0.92).
A possible effect of temperature and artificial saliva was testedfor peanuts and carrots by comparing the d50 obtained in theseassociated conditions with the d50 obtained with tap water at roomtemperature. Values of d50 obtained with or without the associationof temperature at 37 1C and saliva are given in Table 2C. The resultsindicate a significant effect of the temperature–saliva factor(artificial saliva at 37 1C versus tap water at room temperature)[two-way ANOVA, F(1.36)¼9.5;Po0.01] although it was observedonly for peanuts (Po0.01). A significant difference was notedbetween foods but no interaction was observed between food andthe association of temperature at 37 1C and artificial saliva.
The reliability of the AM2 was tested by searching for repeats-related differences between the d50 obtained with all the springsand at all the mastication times. No difference was found betweenrepetitions [three-way ANOVA, F(9.265)¼0.4; P¼0.95], althougha significant difference was evidenced between the two foods andthe three numbers of cycles (Po0.001). No interaction was notedbetween the repeat factor and the other two factors.
4. Discussion
The AM2 makes a bolus similar to the boluses produced byhumans chewing peanuts and carrots. It is reliable, and its variabilityis low, with no difference between repeats. The differences in
ARTICLE IN PRESS
A. Woda et al. / Journal of Biomechanics 43 (2010) 1667–16731672
particle size between foods or between different times within themasticatory sequence were reproduced. However, this involvedchanging the strength of mastication by changing the spring.Another validation approach could use a different property of thefood bolus such as its rheological behavior.
Why use the AM2 rather than human-produced boluses? Thisquestion arises since the mastication device has to be adjusted,recalibration being needed to match changes observed in bolusesat different time points during the masticatory sequence, fordifferent foods types (Peyron et al., 2004) and for groups ofsubjects such as animal or non-healthy human chewers(Mishellany-Dutour et al., 2008; Woda et al., 2010). Thislimitation might be overcome if a feedback system could beadded. Meanwhile, there are many practical uses for the AM2: (i)about half of the bolus mass is lost by the time the ready-to-swallow bolus is collected (Mishellany-Dutour et al., 2008),probably as a result of intermediary deglutitions (Hiiemae andPalmer, 1999), which may change the bolus characteristics bymodifying the proportion of saliva, food fluids and nutrients(Bourdiol et al., 2004). Consequently, the study of food transfor-mation by mastication is biased when the analyses are conductedon boluses collected from subjects. Simulation of mastication bythe AM2 allows the whole nutrient content, including the liquidphase, to be collected at any time during the masticationsequence; although rinsing is technically required for granulo-metric measures, chemical analysis of the bolus liquid phaseproduced by the simulator would not imply rinsing. (ii) The AM2allows bolus formation to be mimicked for non-communicanthuman subjects who frequently have nutritional problems ordysphagia or both. It can also be used to study mastication inother mammals. A rough evaluation of in vivo boluses would beneeded before programming the simulator for studying the effectsof different formulations of the manufactured food on bolusproperties. This would imply a method of bolus collection adaptedto the considered population. (iii) The force sensor monitors forcesdue to both the spring and food resistance. The modifications of theforce due to food resistance can therefore be evaluated. (iv) TheAM2 allows many repeated chewing sequences independentlyof any changes in experimental conditions induced by subjects’compliance limits.
Conflict of interest statement
No conflict of interest.
Acknowledgements
This study was supported by the IFN ‘‘Prix jeune chercheurBernard Beaufr�ere 2006’’ and by the Conseil Regional d’Auvergne.We thank R. Ryan, F. Gallardo and C. Hartmann for their help indrafting.
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