57 BIA BIA cm kg X DEXA BC-418 FFM BIA LR ANN LR r 2 =.897 RMSE=1.678 kg ANN r 2 =.996 RMSE=0.328 kg ANN LR LR ANN DEXA

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1 National Taiwan College of Physical Education THE APPLICATION OF BIOELECTRICAL IMPEDANCE ANALYSIS BY NEURAL NETWORKS APPLIED IN EVALUATION OF BODY COMPOSITION IN ELITE ATHLETES

2 57 BIA BIA cm kg X DEXA BC-418 FFM BIA LR ANN LR r 2 =.897 RMSE=1.678 kg ANN r 2 =.996 RMSE=0.328 kg ANN LR LR ANN DEXA FFM bias 0 kg BC-418 DEXA bias= kg LR ANN BC-418 LR BC-418 ANN DEXA FFM 2 S.D kg ANN LR BC-418 BC-418 X I

3 Wang, Chia-Wei (2010). The application of bioelectrical impedance analysis by neural networks applied in evaluation of body composition in elite athletes, Unpublished master, National Taiwan College of Physical Education. Abstract Bioelectrical impedance analysis (BIA) can estimate body composition easily, rapidly and non-invasively. Some papers have indicated that the accuracy of predictive equations of BIA mainly depend on the equations itself, even, the specific subjects need specified equation. The purpose of this study was to estimate body composition of the football players with the BIA measurement compared to Dual-energy X ray absorptiometry (DEXA). Method: Subjects, 24 football players of National Taiwan College of Physical Education, with mean age at 20.3±1.9 years, mean height at cm and mean weight at kg. To evaluate the accuracy of predictive fat-free mass (FFM) of body composition by bioelectrical impedance analyser (BC-418), DEXA, as criteria method, was compared. By the measured data as factors including the bioelectrical impedance values (Z) of hand-to-foot modulation by BIA in right side, gender, age, height, and weight, the predictive equation by traditional linear regression analysis (LR) for FFM by DEXA was gained, also, the ANN predictive model created. Result: The lower r 2 and greater RMSE in LR (r 2 =.897 and RMSE=1.678 kg) than in ANN (r 2 =.996 and RMSE=0.328 kg) were gained. ANN is better than LR. The biases that FFM of LR and ANN compare to DEXA are about 0 kg. The bias that FFM of BC-418 compares to DEXA is kg. LR and ANN are better than BC-418. The FFM s range of bias (2 SD.) of FFM of LR, BC-418 and ANN compared to DEXA are 3.357, and kg, respectively. ANN is better than LR and BC-418. Conclusion: To estimate body composition of football players, ANN is more applicable than LR and estimated equation of BC-418. Keywords: Bioelectrical impedance analysis (BIA), Artificial neural network (ANN), Dual-energy X-ray absorptiometry (DEXA), fat-free mass (FFM), football player II

4 99 7 III

5 IV...I... II...III... IV... VI...VII BIA FFM...39 FFM

6 ...50 V

7 BIA ~10 r DEXA FFM DEXA BC-418 %BF T DEXA %BF...47 VI

8 DEXA ~10 r FFM BC-418 FFM ANN FFM %BF BC-418 %BF ANN %BF...46 VII

9 health-related fitness body composition molecular (Wang, Pierson, & Heymsfield, 1992) fat mass, FM fat-free mass, FFM Wilmore, (Grundy, 2004; Hubert, Feinleib, McNamara, & Castelli, 1983; Taylor & Baranowski,

10 (Kerruish et al., 2002; Misra et al., 2003; Probst, Goris, Vandereycken, & Coppenolle, 2001) Kireilis Cureton (1947) Body mass index, BMI Brozek, Grande, Anderson Keys (1963) 4 1 Clarys, Martin Drinkwater (1984) underwater weighting, UWW gold standard (Pollock et al., 1976) skinfolds, SF 2

11 (Jackson & Pollock, 1978) bioelectrical impedance analysis, BIA (Powell et al., 2001) X dual-energy X-ray absorptiometry, DEXA X Prior (1997) DEXA DEXA percent of body fat mass, %BF 0.4%BF DEXA (Kohrt, 1998; Mazess, Barden, Bisek, & Hanson, 1990; Svendsen, Haarbo, Hassager, & Christiansen, 1993) Kohrt (1995) DEXA DEXA 20 (V. Heyward, 2001) DEXA DEXA BIA DEXA BIA 3

12 DEXA BIA BIA Backpropagation, BP DEXA BIA DEXA body composition 4

13 bioelectrical impedance analysis, BIA resistance, R R V ρ L²/R V ρ L R fat-free mass, FFM percentage of body fat, %BF 100% 5

14 BIA 1/5 obesity (Grundy, 2004; Hubert et al., 1983; Taylor & Baranowski, 1991) 1 9 Kireillis Cureton (1947) 6

15 (Rico-Sanz, 1998) (Ostojic, 2003; Tsunawake et al., 2003) 2-C two-component molecular model fat mass, FM fat-free mass, FFM 3-C three-component tissue model fat mass, FM bone mineral mass, BMM bone-free lean tissue mass, LTM 3-C three-component cellular model extracellular solids, ECS extracellular fluid, ECF body cell mass 7

16 fluid metabolic model fat extracellular solids, ECS extracellular fluid, ECF intracellular solids, ICS intracellular fluid, ICF C densitometry hydrometry SF BIA 3-C X DEXA 8

17 ECS Fat Fat Fat Bone mineral ECF ECS Fat-free mass Bone-free lean Body cell ECF ICS tissue mass ICF 2-C 3-C 3-C Fluid molecular tissue cellular metabolic model model model model 2-1 anthropometry densitometry skinfolds hydrometry -40 potassium-40 BIA X DEXA near-infrared 9

18 interactance, NIR neutron activation analysis, NAA computerized tomography, CT magnetic resonance imaging, MRI Nieman BMI SKF HD BIA TBW TBP DEXA CT NIR MRI ( Nie man, ) BMI = body mass index; SKF = skinfolds; HD = hydrodensitometry; BIA = bioelectrical impedance analysis; TBW = total body water; TBP = total body potassium; DEXA = dual-energy X-ray absorptiometry; CT = computerized tomography; MRI = magnetic resonance imaging; 1 = ;2 = ; 3 = ; 4 = ; 5 = 10

19 reference methods field reference methods CT MRI NAA DEXA (V. Heyward, 2001) densitometry 2-C FM FFM FM FFM 1.Hydrodensitometry hydrostastic weighing, HD residual volume, RV density of body, Db Goldman and Buskirk equation Db = 11

20 %BF (Brozek et al., 1963) (Siri, 1956) FM FFM 2.Air displacement plethymography ADP 2-C (Brozek et al., 1963; Siri, 1956) 1.FM 0.901g/cc. 2.FFM 1.10g/cc. 3. Fat FFM 4. FM FFM 5. FM FFM 73.8% 19.4% 6.8% hydrometry total body water; TBW TBW 2-C FFM X dual-energy X-ray absorptiometry, 12

21 DEXA 3-C bone mineral mass, BMM bone-free lean tissue mass, LTM fat mass, FM DEXA X X pixel bone mineral mass soft-tissue mass ; lean soft-tissue FM X BMM LTM FM (Bell, Cobner, & Evans, 2000)

22 Pixels containing bone Pixels not containing bone Bone mineral Soft-tissue mass Lean soft-tissue Fat BMM LTM FM FFM 2-2 DEXA Prior 1997 DEXA DEXA %BF 0.4%BF DEXA 20 TBW Kohrt (1995) DEXA DEXA (Kohrt, 1998; Mazess et al., 1990; Svendsen et al., 1993) DEXA field methods BIA SKF SKF BIA 14

23 anthropometry ab C = hip C = (Tran & Weltman, 1989) skinfolds 1915 chest triceps subscapular midaxillary suprailiac abdomoinal thigh 10% Σ 3SKF (Jackson & Pollock, 1978) Fat FFM Siri (1956) Brozek (1963) BIA BIA

24 2-2 FFM FM anthropometric equations 1960~1970 Db total body potassium, TBP NAA CT MRI BIA %BF (Riendeau, Welch, Crisp, Crowley, & Brockett, 1958) Cureton, Hensley Tiburzi (1979) %BF Ostojic (2003) 16

25 Houston (1981) %BF (Davis, Brewer, & Atkin, 1992) V O 2max (Tsunawake et al., 2003) %BF FFM 17

26 (Tahara et al., 2006) BIA resistance, R length, L cross sectional area, A R A L R=ρ L / A ρ resistivity R=ρ / V V=ρ / R

27 A 2-3 reactance, R impedance, Z R ICW ECW R ICW ECW ECW ICW

28 R R ICW ECW 2-4 BIA KHz R Z 2-6 ECW ICW R TBW FFM R R TBW 20

29 FFM %BF 2-2 BIA BIA 21

30 2-2 BIA R^2 SEE 132 Fornetti et al. DEXA; 2-C FFM=0.282 HT BW R Xc kg Hortobagyi, Israel, Houmard, O'Brien et al. HD; 2-C AA:%BF= BMI R ψ CA:%BF= BMI ψ %BF %BF Oppliger,Nielson, Hoegh et al. HD; 2-C FFM= BW HT^2/R kg 110 Yannakoulia et al. DEXA; 2-C FFM=0.247 BW HT^2/R HT kg 42 DEXA=Dual-energy X-ray absorptiometry HD=Hydrodensitometry 2-C= Two-component molecular model HT=height cm ; BW=body weight kg ; R=resistance Ω ; Xc= reactance Ω ; ψ=phase angle; AA= African American CA= Caucasian American (V. H. Heyward & Wagner, 2004) 22

31 BIA BIA (V. Heyward, 2001) BIA (V. H. Heyward & Wagner, 2004) TBW FFM FM (Bunt, Lohman, & Boileau, 1989) 1. RV Db BIA 2. 23

32 10% FM FFM BIA DEXA SKF BIA FM 1.7 kg 2.8 kg FFM 1.7 kg 2.6 kg SKF BIA Stewart & Hannan, CT MRI BIA BIA Z (Malavolti et al., 2003) %BF FM FFM DEXA 24

33 %BF FM FFM DEXA BIA BIA 60% (Kushner, Gudivaka, & Schoeller, 1996) (Deurenberg, Weststrate, Paymans, & van der Kooy, 1988; Oshima & Shiga, 2006) 25

34 (V. H. Heyward & Wagner, 2004) %BF (Jackson, Pollock, Graves, & Mahar, 1988) 1. TBW 2. 26

35 3. 4. BIA BIA (Webster & Barr, 1993) (Jackson et al., 1988) BIA BIA FFM (Pichard, Kyle, Gremion, Gerbase, & Slosman, 1997; Webster & Barr, 1993) 27

36 BIA BIA BIA BIA (Powell et al., 2001) BIA 3853 (Kyle et al., 2001) BIA BIA BIA FFM FFM FFM FM Davis %BF %BF FFM (Davis et al., 1992) BIA SKF BIA BIA BIA BIA FFM %BF (Saunder, Blevins, & Broeder, 1998) BIA 28

37 BIA %BF SKF BIA (Houtkooper, Mullins, Going, Brown, & Lohman, 2001; Stewart & Hannan, 2000) FFM 2.9 kg 6.3 kg BIA FFM (Oppliger, Nielsen, Shetler, Crowley, & Albright, 1992) Lukasku, Bolonchuk, Siders Hall (1990) SEE=2.0 kg Houtkooperet (2001) %BF 4.4%BF 2-2 BIA Eckerson, Housh Johnson (1992) SEE=1.70 kg DEXA FFM 2.3 kg (De Lorenzo et al., 2000) 29

38 1940 Warren McCulloch Walter Pitts 1950 Frank Rosenblatt perceptron network Bernard Widrow Ted Hoff (1960) Widrow-Hoff learning rule Least Mean Square algorithm, LMS 1960 James Anderson (1972) 1980 Backpropagation algorithm David Rumelhart James McClelland 30

39 Feed-Forward Back-Propagation weights biases Inputs b Σ n f Transfer function a output

40 inputs output target weights bias neuron McCulloch & Pitts (1943) transfer function n Hard Limit hardlim Log-Sigmoid logsig

41 2-8 (Ahmed, 2005) 33

42 (Ripley, 1998) Bottaci (1997) , 12, 15, 18, % 12 90% 79% 75% Tafeit, Möller, Sudi Reibnegger (1999) Linder, Mohamed, Lorenzo Pöppl (2003) 34

43 % 4 2 X DEXA GE Lunar Prodigy DEXA en Core2003 Version

44 20 BMM FM FFM 0.5 BIA Tanita, BC-418 Current source electrode Detect electrode 50kz 800µA FM FFM %BF DEXA FFM BC-418 %BF FFM Excel DEXA FFM Pearson r cofficient of determination, r 2 root mean square error, RMSE 36

45 linear weights biases r r 2 RMSE Matlab 2009a log-sigmoid linear neural network toolbox Baysian Regluation BR 1000 multi-start methods weights biases output DEXA FFM target RMSE r 2 RMSE log-sigmoid linear f ( x) = x target output i i r 2 RMSE FFM Bland-Altman plot 37

46 BIA FFM DEXA 38

47 FFM DEXA FFM Excel linear age = Ht = Wt = Z = Pearson r = = RMSE = r 2 hidden neuron, HN r 2 39

48 = r 2 =.897 RMSE = kg RMSE = 1.678kg r 2 1 r ~10 r r RMSE r^ Linear regression number of neurons 4-1 1~10 r 2 r r 2 40

49 FFM BC-418 Bland- Altman plot DEXA FFM X FFM DEXA FFM difference Y FFM DEXA-FFM FFM DEXA-FFM BC-418 %BF FFM DEXA-FFM bias bias+2 SD. bias 2 SD difference FFM of LR-DEXA(kg) bias+2 SD.=3.357 bias=0 bias-2 SD.= DEXA-FFM(kg) 4-2 FFM LR = linear regression DEXA = dual-energy X-ray absorptiometry = LR-DEXA FFM bias = LR-DEXA FFM 2 SD. = 41

50 difference-ffm of BC-418(kg) bias+2 SD.=3.690 bias= bias-2 SD.= DEXA-FFM(kg) 4-3 BC-418 FFM BC-418 = DEXA = dual-energy X-ray absorptiometry = BC418-DEXA FFM bias = BC418-DEXA FFM 2 SD. = difference FFM of ANN-DEXA(kg) bias+2 SD.= bias= bias-2 SD.= DEXA-FFM(kg) 4-4 ANN FFM ANN = DEXA = dual-energy X-ray absorptiometry = ANN-DEXA FFM bias = LR-DEXA FFM 2 SD. = 42

51 4-3 DEXA FFM FFM LR BC-418 ANN bias SD bias + 2 SD bias - 2 SD ANN = BC-418 = DEXA = dual-energy X-ray absorptiometry bias = DEXA FFM 2 SD. = FFM DEXA bias 0 BC-418 FFM kg FFM Oppliger (1992) BIA FFM Pichard (1997) FFM FFM BC-418 2SD kg 2 SD.=0.656 FFM BC-418 DXEA FFM 43

52 BC-418 %BF 2-C FM FFM FFM FM %BF BC %BF DEXA %BF BC DEXA T α =.05 t= p= DEXA BC-418 %BF T Paired Differences DEXA BC418 Mean 97.5% Confidence Interval of the Difference Lower Upper t df Sig. (2-tailed) DEXA = dual-energy X-ray absorptiometry BC-418 = α =.05 T DEXA BC-418 %BF BC-418 %BF Bland- Altman plot DEXA %BF X %BF DEXA FFM difference Y 44

53 %BF DEXA-%BF BC-418 %BF DEXA-%BF %BF DEXA-%BF bias bias+2 SD. bias-2sd difference %BF of LR-DEXA(%) 8 bias+2 SD.= bias= bias-2 SD.= DEXA %BF(%) 4-5 %BF LR = linear regression DEXA = dual-energy X-ray absorptiometry = LR-DEXA %BF bias = LR-DEXA %BF 2 SD. = 45

54 difference %BF of BC-418(%) DEXA %BF of whole body(%) bias+2 SD.=5.945 bias=0.358 bias-2sd.= BC-418 %BF BC-418 = DEXA = dual-energy X-ray absorptiometry = BC418-DEXA %BF bias = BC418-DEXA %BF 2 SD. = difference %BF of ANN-DEXA(%) bias+2 SD.=0.916 bias=0.005 bias-2 SD.= DEXA %BF(%) 4-7 ANN %BF ANN = DEXA = dual-energy X-ray absorptiometry = ANN-DEXA %BF bias = LR-DEXA %BF 2 SD. 46

55 4-5 DEXA %BF %BF LR BC-418 ANN bias SD bias + 2 SD bias - 2 SD ANN = BC-418 = DEXA = dual-energy X-ray absorptiometry bias = DEXA %BF 2 SD. = %BF DEXA %BF bias 0 BC-418 %BF bias DEXA %BF 0.358% 4-4 Oppliger 1992 BIA %BF Hodgdon & Fitzgerald, 1987 Pichard 1997 %BF BC SD.=5.587% 2 SD.=5.170% 2S.D.=0.910% %BF BC-418 DEXA %BF 47

56 BIA V. H. Heyward & Wagner, 2004; Kyle et al., 2004 Oppliger 1992 BIA FFM %BF BC-418 %BF DEXA %BF bias 0.358% BC-418 %BF FFM DEXA FFM bias kg FFM %BF DEXA 0 DEXA FFM bias 0 2 SD kg 2 SD kg FFM DEXA %BF bias 0 2 SD % 2 SD % %BF 48

57 49

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