Table 2.

Summary of the Reliability and Validity of New Methods for Assessing Food and Energy Intake.

Reference	Name of Tool	What Is Measured	Reliability		Validity
			Statistical Method Used	Result	Statistical Method Used	Result
[28]	Automated Wrist Motion Tracking	EI	Sensitivity (true detection rate) = (total true detection)/(total true detection + total undetected bites); Positive Predicted Value (PPV) = (total true detection)/(total true detection + total false detection); compared recorded bites with direct observation.	Control setting: Sensitivity = 94% PPV = 80% Semi-controlled setting: Sensitivity = 86% PPV = 81%	Pearson correlation of EI estimated by device vs. direct observation (r)	R = 0.6
[30]	The bite-based model of kilocalorie intake	EI	Pearson’s correlation of device compared with direct observation; shrinkage value	R = 0.374 Shrinkage value (difference in R2) = 0.014	Independent t test Paired sample t test	Mean estimation error kilocalorie information group: −185 ± 501 kcal; Mean estimation error no kilocalorie information group: −349 ± 748 kcal (p < 0.05); Best human-based estimation (kilocalorie information group) mean estimation error: −257 ± 790 kcal; Bite-based method (predicted formula) mean estimation error: 71 ± 562 kcal; (p < 0.001).
[31]	Automatic Ingestion Monitor (AIM)	EI	N/A	N/A	Accuracy = average between precision (P) and recall (R).	Accuracy of food ingestion = 89.9%, range from 75.82–97.7%.
[32]	Counts of Chews and Swallows Model	EI	A 3-fold cross validation technique, one sided Wilcoxon-Mann-Witney, Bland-Altman analysis and t-Test analysis.	Reporting error for the CCS model was lower than that of the diet diary (p < 0.01). The model underestimated EI. Energy intake estimation had the lowest bias.	A 3-fold cross validation technique, one-sided Wilcoxon-Mann-Witney, Bland-Altman analysis and t-Test analysis.	No statistical differences were found between the CCS model and either diet diary or photographic records.
[33]	Intelligent food-intake monitor	Food intake	Correlation: Proportion of food consumed from sound (auditory based) and image sequence (vision based) compared to the ground truth: proportion of food consumed.	Data not shown	N/A	N/A
[34]	DP + R	EI	Inter-rater reliability coefficients	Error rate ≤5%, Recall assessments ≥0.95	Dependent t-test comparing device to DLW method; Bland-Altman plots; Limits of agreement	Differences between methods in the total sample was not significantly different (DP + R = 2912 ± 661 kcal/day; TDEEDLW = 2849 ± 748 kcal/day, p = 0.42); DP + R was found to overestimate EI compared to TDEEDLW by 63 ± 750 kcal/day (6.8 ± 28%; limits of agreement: −1437, 1564 kcal/day). The Bland-Altman plot indicated no proportional bias variation as a function of the level of EI in the total sample (R = −0.13, p = 0.21).
[35]	RFPM	EI	Bland & Altman analysis	Significant difference: p < 0.0001 between the RFPM and DLW in the standard prompt group. No significant difference in the customized group: p = 0.22. The level of bias in both groups was not influenced by the amount of EI (Adj. R2= −0.03, p = 0.55; Adj. R2 = −0.08, p = 0.78)	Independent sample t-test for error between methods = EI estimated with the RFPM-EI measured with DLW	Significant smaller underestimation in the customized group (270 ± 748 kcal/day or 8.8 ± 29.8%) when compared to the standard prompt group (895 ± 770 kcal/day or 34.3 ± 28.2%), t (33) = −2.35, p < 0.05 with RFPM.
[36]	Real-time Food Recognition System	EI	Test-retest reliability	79.2% classification rate	N/A	N/A
[37]	Snap-n-Eat	Energy/dietary intake	Test-retest reliability	Classification accuracy (% of correctly classified images categories) = 85%	N/A	N/A
[38]	GoCARB	Carb EI	Comparison to actual foods/database	Automatic segmentation (portion size) = 75.4% (86/114); Food item recognition = 85.1% (291/342)	Mean absolute error; Relative error	Mean absolute error = 27.89 (SD 38.20) and 12.28 (SD 9.56) grams of carbohydrates; Mean relative error = 54.8% (SD 72.3%) and 26.2% (SD 18.7%). A significant error between estimations was found (p = 0.001). In general, 60.5% (69/114) of the participants underestimated carbohydrate content.
[39]	Mathematical method	Change in EI	Test-retest reliability; Mean difference	40 kcal/day of mean difference between the gold standard and the mathematical model; No significant difference between the methods for any of the time segments was found (weeks 0–26: p = 0.14; weeks 26–52: p = 0.34; weeks 52–78: p = 0.32; weeks 78–104: p = 0.11).	Paired, 2-sided t test; Pearson correlation (r) Spearman’s corrected (rs)	Change in EI values calculated by the mathematical method or the gold standard DLW/DXA weren’t significantly different; The mathematical model had an accuracy within 132kcal/day for predicting changes in EI; The magnitude of correlation of the change in EI values between models were correlated (weeks 0–26: r = 0.57 (95% confidence interval 0.45, 0.68); p =≤ 0.0001; weeks 78–104: r = 0.19 (0, 0.36); p = 0.05).

¹ N/A = Not applicable.