Abstract

A prototype noninvasive blood glucose level measurement optical device (NI-BGL-MOD) has been developed. The NI-BGL-MOD uses a discrete Fourier transform (DFT) method and a fast artificial neural network (FANN) algorithm to optimize device performance. The appropriate light-emitting diode (LED) for the sensory module was selected based on near-infrared spectrophotometry of a blood glucose model and human blood. DFT is implemented in an analog-to-digital converter (ADC) module. An in vitro trial using the blood glucose model along with a clinical trial involving 110 participants were conducted to evaluate the performance of the prototype. The root-mean-square error (RMSE) of the prototype was 10.8 mg/dl in the in vitro trial and 3.64 mg/dl in the clinical trial, which is lower than the ISO-15197:2016 mandated value of 10 mg/dl. In each trial, consensus error grid analysis (EGA) indicated that the measurement error was within the safe range. The sensitivity and specificity of the prototype were 0.83 (0.36, 1.00) and 0.90 (0.55, 1.00) in the in vitro trial and 0.81 (0.75, 0.85) and 0.83 (0.78, 0.87) in the clinical trial, respectively. In general, the proposed NI-BGL-MOD demonstrated adequate performance compared to gold-standard measurement.

References

References
1.
Finfer
,
S.
,
Wernerman
,
J.
,
Preiser
,
J.-C.
,
Cass
,
T.
,
Desaive
,
T.
,
Hovorka
,
R.
,
Joseph
,
J. I.
,
Kosiborod
,
M.
,
Krinsley
,
J.
,
Mackenzie
,
I.
,
Mesotten
,
D.
,
Schultz
,
M. J.
,
Scott
,
M. G.
,
Slingerland
,
R.
,
Van den Berghe
,
G.
, and
Van Herpe
,
T.
,
2013
, “
Clinical Review: Consensus Recommendations on Measurement of Blood Glucose and Reporting Glycemic Control in Critically III Adults
,”
Crit. Care
,
17
(
3
), p.
229
.10.1186/cc12537
2.
Aravind
,
S.
,
Saboo
,
B.
,
Sadikot
,
S.
,
Shah
,
S. N.
,
Kalra
,
S.
,
Kannampilly
,
J.
,
Kesavadev
,
J.
,
Ghoshal
,
S.
,
Zargar
,
A.
,
Nigam
,
A.
,
Hazra
,
D.
,
Tripathi
,
K.
,
Dharmalingam
,
M.
,
Shah
,
P.
,
Gandhi
,
P.
,
Sahay
,
R.
,
Unnikrishnan
,
R.
,
Gupta
,
S.
,
Bajaj
,
S.
,
Mukhopadhyay
,
S.
, and
Kale
,
S.
,
2015
, “
Consensus Statement on Management of Post-Prandial Hyperglycemia in Clinical Practice in India
,”
J. Assoc. Physicians India
,
63
, p.
14
.
3.
Roglic
,
G.
, and
World Health Organization
, (eds.),
2016
,
Global Report on Diabetes
,
World Health Organization
,
Geneva, Switzerland
.
4.
Kanchi
,
S.
,
Sharma
,
D.
,
Bisetty
,
K.
, and
Nuthalapati
,
V. N.
,
2015
, “
Diabetes and Its Effects: Statistics and Biosensors
,”
J. Env. Anal Chem.
,
2
, p.
e111
.
5.
da Rocha Fernandes
,
J.
,
Ogurtsova
,
K.
,
Linnenkamp
,
U.
,
Guariguata
,
L.
,
Seuring
,
T.
,
Zhang
,
P.
,
Cavan
,
D.
, and
Makaroff
,
L. E.
,
2016
, “
IDF Diabetes Atlas Estimates of 2014 Global Health Expenditures on Diabetes
,”
Diabetes Res. Clin. Pract.
,
117
, pp.
48
54
.10.1016/j.diabres.2016.04.016
6.
Burt
,
M. G.
,
Roberts
,
G. W.
,
Aguilar-Loza
,
N. R.
, and
Stranks
,
S. N.
,
2013
, “
Brief Report: Comparison of Continuous Glucose Monitoring and Finger-Prick Blood Glucose Levels in Hospitalized Patients Administered Basal-Bolus Insulin
,”
Diabetes Technol. Ther.
,
15
(
3
), pp.
241
245
.10.1089/dia.2012.0282
7.
Mussavira
,
S.
,
Dharmalingam
,
M.
, and
Omana Sukumaran
,
B.
,
2015
, “
Salivary Glucose and Antioxidant Defense Markers in Type II Diabetes Mellitus
,”
Turk. J. Med. Sci.
,
45
, pp.
141
147
.10.3906/sag-1306-116
8.
Link
,
M.
,
Schmid
,
C.
,
Pleus
,
S.
,
Baumstark
,
A.
,
Rittmeyer
,
D.
,
Haug
,
C.
, and
Freckmann
,
G.
,
2015
, “
System Accuracy Evaluation of Four Systems for Self-Monitoring of Blood Glucose Following ISO 15197 Using a Glucose Oxidase and a Hexokinase-Based Comparison Method
,”
J. Diabetes Sci. Technol.
,
9
(
5
), pp.
1041
1050
.10.1177/1932296815580161
9.
Marlena Błazik
,
D. G.
,
2014
, “
Improving the Estimation of Meal-Time Insulin Dose Based on the Glycaemic Load of a Meal in Children With Type 1 Diabetes on Insulin Pump Therapy: A Randomized Study
,”
J. Diabetes Metab.
,
5
(
9
).
10.
Salacinski
,
A. J.
,
Alford
,
M.
,
Drevets
,
K.
,
Hart
,
S.
, and
Hunt
,
B. E.
,
2014
, “
Validity and Reliability of a Glucometer Against Industry Reference Standards
,”
J. Diabetes Sci. Technol.
,
8
(
1
), pp.
95
99
.10.1177/1932296813514315
11.
Huch
,
A.
,
Huch
,
R.
, and
Rooth
,
G.
,
1994
, “
Guidelines for Blood Sampling and Measurement of PH and Blood Gas Values in Obstetrics
,”
Eur. J. Obstet. Gynecol. Reprod. Biol.
,
54
(
3
), pp.
165
175
.10.1016/0028-2243(94)90277-1
12.
Yeaw
,
J.
,
Lee
,
W. C.
,
Aagren
,
M.
, and
Christensen
,
T.
,
2012
, “
Cost of Self-Monitoring of Blood Glucose in the United States Among Patients on an Insulin Regimen for Diabetes
,”
J. Manag. Care Pharm.
,
18
(
1
), pp.
21
32
.10.18553/jmcp.2012.18.1.21
13.
Turner
,
A. P. F.
,
2013
, “
Biosensors: Sense and Sensibility
,”
Chem. Soc. Rev.
,
42
(
8
), p.
3184
.10.1039/c3cs35528d
14.
Chowdhury
,
M. K.
,
Srivastava
,
A.
,
Sharma
,
N.
, and
Sharma
,
S.
,
2013
, “
Challenges & Countermeasures in Optical Noninvasive Blood Glucose Detection
,”
Int. J. Innov. Res. Sci. Eng. Technol.
,
2
(
1
), pp.
324
329
.
15.
Vashist
,
S. K.
,
2012
, “
Non-Invasive Glucose Monitoring Technology in Diabetes Management: A Review
,”
Anal. Chim. Acta
,
750
, pp.
16
27
.10.1016/j.aca.2012.03.043
16.
Chowdhury
,
M. K.
,
Srivastava
,
A.
,
Sharma
,
N.
, and
Sharma
,
S.
,
2014
, “
The Potential Application of Amplitude Modulated Ultrasound With Infrared Technique for Blood Glucose Level Determination in Non Invasive Manner
,”
Biomed. Pharmacol. J.
,
7
(
1
), pp.
195
206
.10.13005/bpj/472
17.
Srivastava
,
A.
,
Chowdhury
,
M. K.
,
Sharma
,
S.
, and
Sharma
,
N.
,
2013
, “
Optical Clearance Effect Determination of Glucose by Near Infrared Technique: An Experimental Study Using an Intralipid Based Tissue Phantom
,”
Int. J. Adv. Eng. Technol
,
6
(
3
), pp.
1097
1108
.
18.
Shinde
,
A. A.
, and
Prasad
,
R. K.
,
2011
, “
Non Invasive Blood Glucose Measurement Using NIR Technique Based on Occlusion Spectroscopy
,”
Int. J. Eng. Sci. Technol
,
3
(
12
), pp.
8325
8333
.
19.
McEwen
,
M. P.
, and
Reynolds
,
K. J.
,
2014
, “
Noninvasive Monitoring With Strongly Absorbed Light
,”
Opt. Appl.
,
44
(
2
), pp.
177
190
.
20.
Lawand
,
K.
,
Parihar
,
M.
, and
Patil
,
S. N.
,
2015
, “
Infrared Led Based Non Invasive Blood Glucometer
,”
History
,
44
(
203
), pp.
95
99
.
21.
Ferrante do Amaral
,
C. E.
, and
Wolf
,
B.
,
2008
, “
Current Development in Non-Invasive Glucose Monitoring
,”
Med. Eng. Phys.
,
30
(
5
), pp.
541
549
.10.1016/j.medengphy.2007.06.003
22.
Scholtes-Timmerman
,
M. J.
,
Bijlsma
,
S.
,
Fokkert
,
M. J.
,
Slingerland
,
R.
, and
van Veen
,
S. J.
,
2014
, “
Raman Spectroscopy as a Promising Tool for Noninvasive Point-of-Care Glucose Monitoring
,”
J. Diabetes Sci. Technol.
,
8
(
5
), pp.
974
979
.10.1177/1932296814543104
23.
Baker
,
M. J.
,
Trevisan
,
J.
,
Bassan
,
P.
,
Bhargava
,
R.
,
Butler
,
H. J.
,
Dorling
,
K. M.
,
Fielden
,
P. R.
,
Fogarty
,
S. W.
,
Fullwood
,
N. J.
,
Heys
,
K. A.
,
Hughes
,
C.
,
Lasch
,
P.
,
Martin-Hirsch
,
P. L.
,
Obinaju
,
B.
,
Sockalingum
,
G. D.
,
Sulé-Suso
,
J.
,
Strong
,
R. J.
,
Walsh
,
M. J.
,
Wood
,
B. R.
,
Gardner
,
P.
, and
Martin
,
F. L.
,
2014
, “
Using Fourier Transform IR Spectroscopy to Analyze Biological Materials
,”
Nat. Protoc.
,
9
(
8
), pp.
1771
1791
.10.1038/nprot.2014.110
24.
Hossain
,
E.
,
Bannerman
,
P. L.
, and
Jeffery
,
D. R.
,
2011
, “
Scrum Practices in Global Software Development: A Research Framework
,”
PROFES
,
Springer
,
Berlin
, pp.
88
102
.
25.
Jenie
,
R. P.
,
2011
, “
Development of Alternative to Pressman Standard on Small Solution Development, Case: Bina Nusantara Theses Student
,”
International Conference on Advances in Computing, Control, and Telecommunication Technologies
,
Jakarta, Indonesia
,
Dec. 13–14
, pp.
123
126
.
26.
Rawal
,
S.
,
Manning
,
P.
, and
Katare
,
R.
,
2014
, “
Cardiovascular MicroRNAs: As Modulators and Diagnostic Biomarkers of Diabetic Heart Disease
,”
Cardiovasc. Diabetol.
,
13
(
1
), p.
44
.10.1186/1475-2840-13-44
27.
Bao
,
Y.-G.
, and
Wang
,
S.
,
2017
, “
Labeled Von Neumann Architecture for Software-Defined Cloud
,”
J. Comput. Sci. Technol.
,
32
(
2
), pp.
219
223
.10.1007/s11390-017-1716-0
28.
Abd Ali
,
J.
,
Hannan
,
M. A.
,
Mohamed
,
A.
,
Shareef
,
H.
, and
Hussein Mutlag
,
A.
,
2015
, “
Performance Development of Space Vector Pulse Width Modulation for Induction Motor Drive Using Artificial Intelligence
,”
Appl. Mech. Mater.
,
785
, pp.
146
150
.10.4028/www.scientific.net/AMM.785.146
29.
Nikolić
,
M.
,
Jović
,
A.
,
Jakić
,
J.
,
Slavnić
,
V.
, and
Balaž
,
A.
,
2014
, “
An Analysis of FFTW and FFTE Performance
,”
High-Performance Computing Infrastructure for South East Europe's Research Communities
,
M.
Dulea
,
A.
Karaivanova
,
A.
Oulas
,
I.
Liabotis
,
D.
Stojiljkovic
, and
O.
Prnjat
, (eds.),
Springer International Publishing
,
Cham, Switzerland
, pp.
163
170
.
30.
Clarke
,
W. L.
,
Cox
,
D.
,
Gonder-Frederick
,
L. A.
,
Carter
,
W.
, and
Pohl
,
S. L.
,
1987
, “
Evaluating Clinical Accuracy of Systems for Self-Monitoring of Blood Glucose
,”
Diabetes Care
,
10
(
5
), pp.
622
628
.10.2337/diacare.10.5.622
31.
Parkes
,
J. L.
,
Slatin
,
S. L.
,
Pardo
,
S.
, and
Ginsberg
,
B. H.
,
2000
, “
A New Consensus Error Grid to Evaluate the Clinical Significance of Inaccuracies in the Measurement of Blood Glucose
,”
Diabetes Care
,
23
(
8
), pp.
1143
1148
.10.2337/diacare.23.8.1143
32.
Cherry
,
A. L.
, and
Dillon
,
M. E.
,
2013
, “
The AC-OK Cooccurring Screen: Reliability, Convergent Validity, Sensitivity, and Specificity
,”
J. Addict.
, pp.
1
8
.10.1155/2013/573906
33.
Juneja
,
A.
, and
Sharma
,
S.
,
2015
, “
Issues of Sample Size in Sensitivity and Specificity Analysis With Special Reference to Oncology
,”
J. Cancer Res. Ther.
,
11
(
2
), p.
482
.10.4103/0973-1482.139396
34.
Schmolze
,
D. B.
,
Horowitz
,
G. L.
, and
Tolan
,
N. V.
,
2016
, “
Using Point of Care Glucose Meters in the Critically—III: Assessing Meter Performance in the Clinical Context
,”
Point Care
,
15
(
4
), pp.
137
143
.10.1097/POC.0000000000000107
35.
Moher
,
D.
,
Hopewell
,
S.
,
Schulz
,
K. F.
,
Montori
,
V.
,
Gotzsche
,
P. C.
,
Devereaux
,
P. J.
,
Elbourne
,
D.
,
Egger
,
M.
, and
Altman
,
D. G.
,
2010
, “
CONSORT 2010 Explanation and Elaboration: Updated Guidelines for Reporting Parallel Group Randomised Trials
,”
BMJ
,
340
, p.
c869
.10.1136/bmj.c869
36.
Mitsios
,
J. V.
,
Ashby
,
L. A.
,
Haverstick
,
D. M.
,
Bruns
,
D. E.
, and
Scott
,
M. G.
,
2013
, “
Analytic Evaluation of a New Glucose Meter System in 15 Different Critical Care Settings
,”
J. Diabetes Sci. Technol.
,
7
(
5
), pp.
1282
1287
.10.1177/193229681300700518
37.
Karon
,
B. S.
,
Blanshan
,
C. T.
,
Deobald
,
G. R.
, and
Wockenfus
,
A. M.
,
2014
, “
Retrospective Evaluation of the Accuracy of Roche AccuChek Inform and Nova StatStrip Glucose Meters When Used on Critically III Patients
,”
Diabetes Technol. Ther.
,
16
(
12
), pp.
828
832
.10.1089/dia.2014.0074
38.
Bailey
,
T. S.
,
Chang
,
A.
, and
Christiansen
,
M.
,
2015
, “
Clinical Accuracy of a Continuous Glucose Monitoring System With an Advanced Algorithm
,”
J. Diabetes Sci. Technol.
,
9
(
2
), pp.
209
214
.10.1177/1932296814559746
39.
McLaughlin
,
T.
,
Abbasi
,
F.
,
Cheal
,
K.
,
Chu
,
J.
,
Lamendola
,
C.
, and
Reaven
,
G.
,
2003
, “
Use of Metabolic Markers to Identify Overweight Individuals Who Are Insulin Resistant
,”
Ann. Intern. Med.
,
139
(
10
), pp.
802
809
.10.7326/0003-4819-139-10-200311180-00007
40.
Bennett
,
C. M.
,
Guo
,
M.
, and
Dharmage
,
S. C.
,
2007
, “
HbA 1c as a Screening Tool for Detection of Type 2 Diabetes: A Systematic Review
,”
Diabet. Med.
,
24
(
4
), pp.
333
343
.10.1111/j.1464-5491.2007.02106.x
41.
Wang
,
X.
,
Ioacara
,
S.
, and
DeHennis
,
A.
,
2015
, “
Long-Term Home Study on Nocturnal Hypoglycemic Alarms Using a New Fully Implantable Continuous Glucose Monitoring System in Type 1 Diabetes
,”
Diabetes Technol. Ther.
,
17
(
11
), pp.
780
786
.10.1089/dia.2014.0375
42.
Bhavadharini
,
B.
,
Mahalakshmi
,
M. M.
,
Maheswari
,
K.
,
Kalaiyarasi
,
G.
,
Anjana
,
R. M.
,
Deepa
,
M.
,
Ranjani
,
H.
,
Priya
,
M.
,
Uma
,
R.
,
Usha
,
S.
,
Pastakia
,
S. D.
,
Malanda
,
B.
,
Belton
,
A.
,
Unnikrishnan
,
R.
,
Kayal
,
A.
, and
Mohan
,
V.
,
2016
, “
Use of Capillary Blood Glucose for Screening for Gestational Diabetes Mellitus in Resource-Constrained Settings
,”
Acta Diabetol.
,
53
(
1
), pp.
91
97
.10.1007/s00592-015-0761-9
43.
Uemura
,
M.
,
Yano
,
Y.
,
Suzuki
,
T.
,
Yasuma
,
T.
,
Sato
,
T.
,
Morimoto
,
A.
,
Hosoya
,
S.
,
Suminaka
,
C.
,
Nakajima
,
H.
,
Gabazza
,
E. C.
, and
Takei
,
Y.
,
2017
, “
Comparison of Glucose Area Under the Curve Measured Using Minimally Invasive Interstitial Fluid Extraction Technology With Continuous Glucose Monitoring System in Diabetic Patients
,”
Diabetes Metab. J.
,
41
(
4
), p.
265
.10.4093/dmj.2017.41.4.265
44.
DuBois
,
J. A.
,
Slingerland
,
R. J.
,
Fokkert
,
M.
,
Roman
,
A.
,
Tran
,
N. K.
,
Clarke
,
W.
,
Sartori
,
D. A.
,
Palmieri
,
T. L.
,
Malic
,
A.
,
Lyon
,
M. E.
, and
Lyon
,
A. W.
,
2017
, “
Bedside Glucose Monitoring—Is It Safe? A New, Regulatory-Compliant Risk Assessment Evaluation Protocol in Critically III Patient Care Settings
,”
Crit. Care Med.
,
45
(
4
), pp.
567
574
.10.1097/CCM.0000000000002252
45.
Prabhudesai
,
S.
,
Kanjani
,
A.
,
Bhagat
,
I.
,
Ravikumar
,
K. G.
, and
Ramachandran
,
B.
,
2015
, “
Accuracy of a Real-Time Continuous Glucose Monitoring System in Children With Septic Shock: A Pilot Study
,”
Indian J. Crit. Care Med. Peer-Rev. Off. Publ. Indian Soc. Crit. Care Med.
,
19
(
11
), p.
642
.10.4103/0972-5229.169331
46.
Goodarzi
,
M.
,
Sharma
,
S.
,
Ramon
,
H.
, and
Saeys
,
W.
,
2015
, “
Multivariate Calibration of NIR Spectroscopic Sensors for Continuous Glucose Monitoring
,”
Trends Anal. Chem.
,
67
, pp.
147
158
.10.1016/j.trac.2014.12.005
47.
Ryckeboer
,
E.
,
Bockstaele
,
R.
, and
Baets
,
R.
,
2013
, “
Absorption Spectroscopy of Glucose Based on a Silicon Photonics Evanescent Sensor
,”
IEEE Photonics Conference
,
Sept. 8–12
,
Bellevue, WA
, pp.
163
164
.
48.
Lopes
,
J. A.
, and
de Toledo Fleury
,
A.
,
1999
, “
Mathematical Modeling of Blood Glucose Metabolism and the Artificial Pancreas Development
,”
XV Congresso Brasileiro de Engenharia Mecanica
,
Nov. 22–26
,
Sao Paulo, Brasil
.
49.
Jenie
,
R. P.
,
Iskandar
,
J.
,
Kurniawan
,
A.
,
Rustami
,
E.
,
Syafutra
,
H.
,
Nurdin
,
N. M.
,
Handoyo
,
T.
,
Prabowo
,
J.
,
Febryarto
,
R.
,
Rahayu
,
M. S. K.
,
Damayanthi
,
E.
,
Rimbawan
,
Sukandar
,
D.
,
Suryana
,
Y.
,
Irzaman
., and
Alatas
,
H.
,
2017
, “
Proposed Application of Fast Fourier Transform in Near Infra Red Based Non Invasive Blood Glucose Monitoring System
,”
IOP Conf. Ser. Earth Environ. Sci.
,
58
, p.
012011
.10.1088/1755-1315/58/1/012011
50.
Freckmann
,
G.
,
Schmid
,
C.
,
Baumstark
,
A.
,
Pleus
,
S.
,
Link
,
M.
, and
Haug
,
C.
,
2012
, “
System Accuracy Evaluation of 43 Blood Glucose Monitoring Systems for Self-Monitoring of Blood Glucose According to DIN EN ISO 15197
,”
J. Diabetes Sci. Technol.
,
6
(
5
), pp.
1060
1075
.10.1177/193229681200600510
51.
Sobel
,
S. I.
,
Chomentowski
,
P. J.
,
Vyas
,
N.
,
Andre
,
D.
, and
Toledo
,
F. G.
,
2014
, “
Accuracy of a Novel Noninvasive Multisensor Technology to Estimate Glucose in Diabetic Subjects During Dynamic Conditions
,”
J. Diabetes Sci. Technol.
,
8
(
1
), pp.
54
63
.10.1177/1932296813516182
52.
Laffel
,
L.
,
2016
, “
Improved Accuracy of Continuous Glucose Monitoring Systems in Pediatric Patients With Diabetes Mellitus: Results From Two Studies
,”
Diabetes Technol. Ther.
,
18
(
S2
), pp.
S2-23
S2-33
.
53.
Thabit
,
H.
,
Leelarathna
,
L.
,
Wilinska
,
M. E.
,
Elleri
,
D.
,
Allen
,
J. M.
,
Lubina-Solomon
,
A.
,
Walkinshaw
,
E.
,
Stadler
,
M.
,
Choudhary
,
P.
,
Mader
,
J. K.
,
Dellweg
,
S.
,
Benesch
,
C.
,
Pieber
,
T. R.
,
Arnolds
,
S.
,
Heller
,
S. R.
,
Amiel
,
S. A.
,
Dunger
,
D.
,
Evans
,
M. L.
, and
Hovorka
,
R.
,
2015
, “
Accuracy of Continuous Glucose Monitoring During Three Closed-Loop Home Studies Under Free-Living Conditions
,”
Diabetes Technol. Ther.
,
17
(
11
), pp.
801
807
.10.1089/dia.2015.0062
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