Validity of estimating physical activity intensity using a triaxial accelerometer in healthy adults and older adults

BackgroundA triaxial accelerometer with an algorithm that could discriminate locomotive and non-locomotive activities in adults has been developed. However, in the elderly, this accelerometer has not yet been validated. The aim were to examine the validity of this accelerometer in the healthy elderly, and to compare the results with those derived in a healthy younger sample.MethodsTwenty-nine healthy elderly subjects aged 60–80 years (Elderly), and 42 adults aged 20–59 years (Younger) participated. All subjects performed 11 activities, including locomotive and non-locomotive activities with a Douglas bag while wearing the accelerometer (Active style Pro HJA-750C). Physical activity intensities were expressed as metabolic equivalents (METs). The relationship between the METs measured using the Douglas bag and METs predicted using the accelerometer was evaluated.ResultsA significant correlation between actual and predicted METs was observed in both Elderly (r=0.85, p<0.001) and Younger (r=0.88, p<0.001). Predicted METs significantly underestimated compared with actual METs in both groups (p<0.001). The mean of the errors was −0.6±0.6 METs in Elderly and −0.1±0.5 METs in Younger. The degree of underestimation increased with increasing METs in Elderly (p<0.001). A stepwise multiple regression analysis revealed that predicted METs, age, and weight were related to actual METs in both groups.ConclusionThe degree of correlation between predicted and actual METs was comparable in elderly and younger participants, but the prediction errors were greater in elderly participants, particular at higher-intensity activities, which suggests that different predicting equations may be needed for the elderly.

Abstract 279: Cardiac Arrest is Associated With a Global Level Alteration in Oxygen Metabolism: A Clinical Pilot Study

Objective: We recently reported that a global-level metabolic alteration occurs after cardiac arrest (CA) in our high fidelity rodent model. The finding was that dissociation of O 2 consumption (VO 2 ) and carbon dioxide generation (VCO 2 ) resulted in a respiratory quotient (RQ: calculated by dividing VCO 2 by VO 2 ) that fell well outside the normally cited range of 0.7-1.0. We hypothesized that a lowered RQ is similarly found in human CA patients. Methods: The study consisted of three subject groups: 1) healthy volunteer, 2) post-surgical patient (control) and 3) post-CA patient. We measured the VO 2 and VCO 2 of mechanically ventilated subjects using the Douglas bag method. Inspiration and expiration gas samples were collected in two separate bags . and RQ was calculated from CO 2 and O 2 gas concentrations in the samples. The patients and healthy volunteers were ventilated using the same model mechanical ventilator. Alert healthy volunteers bit onto a mouthpiece and the samples were collected, while post-surgical and post-CA patients were unconscious during the measurements. We measured the RQ of healthy volunteers at normal and high fractions of inspired oxygen (FIO 2 ) in order to test the validity of our methods at various inspired O 2 levels. Results: The RQs of the three healthy volunteers were 0.83, 0.92 and 0.85 at an FIO 2 of 0.21 and 0.86, 0.88, and 0.83 at an FIO 2 of 0.90 respectively. The RQs of the two post-surgical patients were 0.92 and 0.88 at an FIO 2 of 0.5. None of the post-surgical patients had any complications following the surgery and all were discharged. The RQ of a post-CA patient measured 2.5 hours after the CA was found to be 0.72 at an FIO 2 of 0.9. The CA patient expired within 24 hours of hospital admission. Conclusions: The same trend between the findings of both our rodent study and the CA patient suggest that resuscitation from CA alters cellular metabolism on a global level. This metabolic alteration in turn causes the dissociation of O 2 consumption and CO 2 generation resulting in a lowered RQ. Our findings warrant a larger clinical study to confirm a lowered RQ in post-CA patients and bench work to elucidate the causative mechanism of this relationship.

Breathing resistance in automated metabolic systems is high in comparison with the Douglas Bag method and previous recommendations

The purpose of this study was to investigate the resistance to breathing in metabolic systems used for the distribution and measurement of pulmonary gas exchange. A mechanical lung simulator was used to standardize selected air flow rates ([Formula: see text], L/s). The delta pressure (Δ p, Pa) between the ambient air and the air inside the equipment was measured in the breathing valve’s mouthpiece adapter for four metabolic systems and four types of breathing valves. Resistance for the inspiratory and expiratory sides was calculated as RES = (Δ p/[Formula: see text]) Pa/L/s. The results for resistance showed significant ( p < 0.05) between-group variance among the tested metabolic systems, breathing valves, and between most of the completed [Formula: see text]. The lowest resistance among the metabolic systems was found for a Douglas Bag system which had approximately half of the resistance compared to the automated metabolic systems. The automated systems were found to have higher resistance even at low [Formula: see text] in comparison with previous findings and recommendations. For the hardware components, the highest resistance was found for the breathing valves, while the lowest resistance was found for the hoses. The results showed that resistance in metabolic systems can be minimized through conscious choices of system design and hardware components.

The Ventilation-Corrected ParvoMedics TrueOne 2400 Provides a Valid and Reliable Assessment of Resting Metabolic Rate (RMR) in Athletes Compared With the Douglas Bag Method

The aim of the current study was to determine if a single ParvoMedics TrueOne 2400 metabolic cart provides valid and reliable measurement of RMR in comparison with the criterion Douglas Bag method (DB). Ten endurance-trained participants completed duplicate RMR measurements on 2 consecutive days using the ParvoMedics system in exercise mode, with the same expirate analyzed using DB. Typical error (TE) in mean RMR between the systems was 578.9 kJ or 7.5% (p = .01). In comparison with DB, the ParvoMedics system over-estimated RMR by 946.7 ± 818.6 kJ. The bias between systems resulted from ParvoMedics VE(STPD) values. A regression equation was developed to correct the bias, which reduced the difference to -83.3 ± 631.9 kJ. TE for the corrected ParvoMedics data were 446.8 kJ or 7.2% (p = .70). On Day 1, intraday reliability in mean RMR for DB was 286.8 kJ or 4.3%, (p = .54) and for ParvoMedicsuncorrected, 359.3 kJ or 4.4%, (p = .35), with closer agreement observed on Day 2. Interday reliability for DB was 455.3 kJ or 6.6% (p = .61) and for ParvoMedicsuncorrected, 390.2 kJ or 6.3% (p = .54). Similar intraday and interday TE was observed between ParvoMedicsuncorrected and ParvoMedicscorrected data. The ParvoMedics TrueOne 2400 provided valid and reliable RMR values compared with DB when the VE(STPD) error was corrected. This will enable widespread monitoring of RMR using the ParvoMedics system in a range of field-based settings when DB is not available.

Comparison Between Aerobic Power Parameters at Different Time- Averaging Intervals in Swimming: An Update

Sousa et al. (Open Sports Sci J, 3: 22 – 24, 2010) showed that different time averaging intervals lead to distinct VO2 values in a maximal 200m front crawl effort, evidencing higher VO2 values for breath-by-breath sampling, and differences between this latter data acquisition and all the other less frequent time intervals studied (5, 10, 15 and 20 s). These are interesting outputs in the field of exercise physiology applied to swimming once: (1) VO2 assessment is conducted in a swimming pool with a portable gas analyser which allowed breath-by-breath measurements, and not in a swimming flume with a Douglas bag technique or mixing chamber analyser, as traditionally occurs, and (2) the comparison between different time-averaging intervals used to remove breath-by-breath fluctuations during exercise periods has remained neglected, in sport in general and swimming in particular. Therefore, in the present study, we investigate the influence that different time averaging intervals have in aerobic power related parameters (VO2peak and VO2max). Ten subjects performed 200m front crawl effort at supra-maximal intensities (all-out test) and other ten subjects performed 200m front crawl effort at maximal aerobic intensities (100% of VO2max).The intensity at which the 200m front crawl was performed (supra-maximal and maximal intensities) had a significant effect on VO2peak and VO2max values obtained for each averaging intervals studied.

Examination of the Moxus Modular Metabolic System by the Douglas-bag technique

The purpose of this study was to examine the performance of the Moxus Modular Metabolic System from AEI Technologies, Inc. using the Douglas-bag method as reference. To achieve this, eight moderately trained subjects cycled for 5 min at constant powers from 50 to 300 W in increments of 50 W. The O2 uptake was measured simultaneously by both systems during the last minute of each stage. The O2 uptake reported by the Moxus system was 83 ± 78 mL·min–1 higher (mean ± SD; ≈3%, +62 µmol·s–1, P < 0.001) than that reported by the Douglas-bag method; the bias varied by ≈2% between the subjects. The higher O2 uptake of the Moxus system was a consequence of 1.4% ± 3.0% higher reported ventilation and 2% ± 3% higher reported O2 extraction per volume of air breathed. The respiratory exchange ratio (R value) reported by the Moxus system rose proportionally to that of the Douglas-bag method and was 1% ± 2% higher for the range examined (0.75–1.10). Repeated tests of the maximal O2 uptake showed a variability (coefficient of variation) of 2.5%. The study concluded that measurements by the Moxus system showed some bias and residual variation and, in addition, some systematic differences between the subjects in the O2 uptake. The R value was reported quite accurately with moderate random error. Although there were some computer software and hardware instability problems that need to be solved, the Moxus system worked quite well and provided data more reliable than those of most commercial instruments.

Validation and Comparison of 3 Accelerometers for Measuring Physical Activity Intensity During Nonlocomotive Activities and Locomotive Movements

Background:The current study evaluated the validity of 3 commercially-available accelerometers to assess metabolic equivalent values (METs) during 12 activities.Methods:Thirty-three men and thirty-two women were enrolled in this study. The subjects performed 5 nonlocomotive activities and 7 locomotive movements. The Douglas bag method was used to gather expired air. The subjects also wore 3 hip accelerometers, a Lifecorder uniaxial accelerometer (LC), and 2 triaxial accelerometers (ActivTracer, AT; Actimarker, AM).Results:For nonlocomotive activities, the LC largely underestimated METs for all activities (20.3%–55.6%) except for desk work. The AT overestimated METs for desk work (11.3%) and hanging clothes (11.7%), but underestimated for vacuuming (2.3%). The AM underestimated METs for all nonlocomotive activities (8.0%–19.4%) except for hanging clothes (overestimated by 16.7%). The AT and AM errors were significant, but much smaller than the LC errors (23.2% for desk work and –22.3 to –55.6% for the other activities). For locomotive movements, the 3 accelerometers significantly underestimated METs for all activities except for climbing down stairs.Conclusions:We conclude that there were significant differences for most activities in 3 accelerometers. However, the AT, which uses separate equations for nonlocomotive and locomotive activities, was more accurate for nonlocomotive activities than the LC.