OBJECTIVE: To accurately measure human energy metabolism with high temporal resolution, a respiratory gas analysis system was designed using a breath-by-breath approach. METHODS: Firstly, indirect calorimetry was employed in respiratory gas analysis to measure the respiratory flow and concentration signals in real-time. Secondly, oxygen consumption QO2 and carbon dioxide production QCO2 were calculated through respiratory characteristic alignment and respiratory signal segmentation. Finally, metabolic indexes were calculated according to the Weir formula. Furthermore, a controlled trial was formulated for validation comparisons with the MGC ULTIMA SYSTEM PFX CARDIO2. RESULTS: The results indicate that the data points of metabolic indexes measured by this system all fall within the confidence interval when compared with those of the MGC. CONCLUSION The system has high consistency with the MGC measurement results. Thus, the system can accurately measure metabolism in real-time and provide data support for clinical nutrition assessment and therapy.
Humans ; Energy Metabolism ; Breath Tests/instrumentation* ; Calorimetry, Indirect/instrumentation* ; Equipment Design

OBJECTIVEUsing doubly labeled water method to validate the colmputer science application's activity monitor (CSA) in assessing physical activity of free-living adults in Beijing, in order to develop equations to predict total daily energy expenditure (TEE) and activity related energy expenditure (AEE) from activity counts (AC) and anthropometric variables.

METHODSA total of 72 healthy adults (33 males and 39 females, mean age 43.6 +/- 4.0 yr) were monitored for 7 consecutive days by CSA. TEE was simultaneously measured using doubly labeled water method. Average AC (counts/min(-1)) was compared with TEE, AEE and physical activity level (PAL).

RESULTSPhysical activity determined by AC was significantly related to data on energy expenditures: TEE (r = 0.31, P < 0.01), AEE (r = 0.30, P < 0.05), and PAL (r = 0.26, P < 0.05). Multiple stepwise regression analysis showed that TEE was significantly influenced by gender, fat-free mass (FFM) or BMI and AC (R(2) = 0.52 - 0.70) while AEE was significantly influenced by gender, FFM and AC (R(2) = 0.25 - 0.32).

CONCLUSIONAC from CSA activity monitor seemed a useful measure in studying the total amount of physical activity in free-living adults while AC significantly contributed to the explained variation in TEE and AEE.

Activities of Daily Living ; Adult ; Anthropometry ; Body Weight ; Calorimetry, Indirect ; Energy Metabolism ; physiology ; Female ; Humans ; Male ; Monitoring, Physiologic ; instrumentation ; Motor Activity ; physiology ; Physical Fitness ; physiology