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Cardiorespiratory fitness plays an important role in coping with hypoxic stress at high altitudes. However, the association of cardiorespiratory fitness with the development of acute mountain sickness (AMS) has not yet been evaluated. Wearable technology devices provide a feasible assessment of cardiorespiratory fitness, which is quantifiable as maximum oxygen consumption (VO_{2}max) and may contribute to AMS prediction.
We aimed to determine the validity of VO_{2}max estimated by the smartwatch test (SWT), which can be selfadministered, in order to overcome the limitations of clinical VO_{2}max measurements. We also aimed to evaluate the performance of a VO_{2}maxSWT–based model in predicting susceptibility to AMS.
Both SWT and cardiopulmonary exercise test (CPET) were performed for VO_{2}max measurements in 46 healthy participants at low altitude (300 m) and in 41 of them at high altitude (3900 m). The characteristics of the red blood cells and hemoglobin levels in all the participants were analyzed by routine blood examination before the exercise tests. The BlandAltman method was used for bias and precision assessment. Multivariate logistic regression was performed to analyze the correlation between AMS and the candidate variables. A receiver operating characteristic curve was used to evaluate the efficacy of VO_{2}max in predicting AMS.
VO_{2}max decreased after acute high altitude exposure, as measured by CPET (25.20 [SD 6.46] vs 30.17 [SD 5.01] at low altitude;
Our study demonstrates that the smartwatch device can be a feasible approach for estimating VO_{2}max. In both low and high altitudes, VO_{2}maxSWT showed a systematic bias toward a calibration point, slightly overestimating the proper VO_{2}max when investigated in healthy participants. The SWTbased VO_{2}max at low altitude is an effective indicator of AMS and helps to better identify susceptible individuals following acute highaltitude exposure, particularly by combining the RDWCV at low altitude.
Chinese Clinical Trial Registry ChiCTR2200059900; https://www.chictr.org.cn/showproj.html?proj=170253
In recent years, mountain climbing has become a popular activity for pleasure, work, and athletic competitions. However, inadequate acclimatization to hypobaric hypoxia results in a series of symptoms known as acute mountain sickness (AMS). AMS is relatively common among new travelers, affecting >30% of individuals ascending to 3500 m and >70% of those ascending above 6000 m [
Maximum oxygen consumption (VO_{2}max) is defined as the maximum capacity of the cardiovascular, respiratory, and muscular systems to deliver and utilize oxygen, which is reflected by an individual’s cardiorespiratory fitness [
VO_{2}max decreases during acute or chronic exposure to high altitudes, which is mainly attributed to the reduction of PO_{2} [
We recruited 46 healthy adults (27 women and 19 men, age range 2254 years) from Chongqing, China, based on the inclusion and exclusion criteria. All participants had lived at low altitudes (<500 m) for at least 10 years and had no recent history of highaltitude (>2500 m) exposure (in the last 6 months). Participants with any one of the following conditions were excluded: respiratory and cardiovascular diseases, malignant tumors, liver and kidney dysfunctions, and psychiatric disorders or neuroses that would not allow them to complete the questionnaires.
The study protocol (ChiCTR2200059900) complied with the Declaration of Helsinki and was approved by the ethics committee of Xinqiao Hospital of Army Medical University (approval: 2022研第06001). Written informed consent was obtained from all the participants after the study details, procedures, benefits, and risks were explained.
This study consisted of 2 exercise tests at low and high altitudes (
Cohort development diagram for this study. AMS, acute mountain sickness; CPET, cardiopulmonary exercise test; SWT, smartwatch test.
The participants were required to avoid eating or drinking anything (fasting) apart from water for up to 12 hours. Approximately 5 mL of intravenous blood was collected from the inside of the elbow and mixed with 1 mL of dipotassium ethylenediaminetetraacetic acid anticoagulant by using a tight band (tourniquet). Blood samples were analyzed using a BC3000 plus automated hematology corpuscle analyzer (Mindray). The details of the 19 different parameters are presented in
The CPET was performed on an electronically braked cycle ergometer (EC3000e, Customed) in an erect position with breathbybreath measurements through a tightly fitted face mask of minute ventilation, O_{2} uptake, and CO_{2} output by using a cardiopulmonary exercise testing system (Metalyzer 3B, Cortex). Before performing CPET, the baseline physiological measures for all devices used in this study were measured for 5 minutes in a resting state and subsequently in a standing position. After the baseline measurement, the test was conducted immediately. The cycle ergometry test protocol included 3 minutes of freewheel cycling and subsequently proceeded with a continual increase in resistance by 25 W/min (according to the prior known exercise capacity [
We provided participants with a smartwatch (Huawei Watch GT Runner) and instructed them to wear it correctly on the left wrist, which enables reliable and persistent measurement of running speed, distance, and heart rate. Therefore, these measurements could be monitored continuously and automatically during each running activity, stored on the participant’s mobile device (Huawei MatePad 11 DBYW09), and regularly transmitted to a secure cloud server, which was later transferred to the Huawei Health Center software through Bluetooth. Specifically, VO_{2}max estimation steps were as follows: (1) the personal background information (age, height, and weight) of the participant was logged in and the exercise type (running outdoors) was selected; (2) the participant started to run with a smartwatch that measured the heart rate and speed on level ground; (3) the start and end points were in the same place, and the smartwatch was stopped by the researchers uniformly with a timely click; (4) the researchers subsequently saved the participants’ running data to an album on the pad, facilitating further statistical analysis; and (5) the smartwatch and mobile device were formatted to prepare for the next test.
The signal processing by Huawei Watch GT Runner is licensed by the Firstbeat Technology’s Fitness Test, which is based on intelligent detection for both data reliability and exercise pattern during successive recording [
The presence of AMS at high altitude was assessed using the Lake Louise consensus scoring system 2018 version [
Categorical variables were described as numbers and percentages. Descriptive statistics were presented as mean (SD) for variables with skewed distribution and median (IQR) for variables with normal distribution. The Mann–Wilcoxon ranksum, independentsample
The relationship between the variables and AMS was examined by binomial logistic regression analysis with univariate analyses. The relationship between VO_{2}maxCPET, VO_{2}maxSWT, RDWCV, and AMS was further examined by multivariate analyses. In the preliminary screening, we considered the variable with
A total of 46 participants were recruited for this study, of whom 20 (44%) participants developed AMS. The clinical characteristics of participants with AMS and without AMS are presented in
Baseline characteristics, blood routine test, and maximum oxygen consumption of the participants at low altitudes.
Variables  Total (n=46)  Participants with AMS^{a} (n=20)  Participants without AMS (n=26)  



Age (years), mean (SD)  33.33 (7.80)  33.85 (8.41)  32.92 (7.44)  .70  


.17  


Female  27 (59)  14 (70)  13 (50) 



Male  19 (41)  6 (30)  13 (50) 


BMI (kg/m^{2}), median (IQR)  22.19 (20.2223.64)  21.89 (20.1523.44)  22.40 (20.2224.01)  .78  


.18  


Current drinker or exdrinker  10 (22)  2 (10)  8 (31) 



Never  36 (78)  18 (90)  18 (69) 



.92  


Current smoker or exsmoker  6 (13)  2 (10)  4 (15) 



Nonsmoker  40 (87)  18 (90)  22 (85) 


HR^{c} (beats/min), mean (SD)  78.93 (9.69)  81.25 (9.72)  77.15 (9.46)  .16  

SpO_{2}^{d} (%), median (IQR)  97 (9698)  97 (9698.75)  97 (9698)  .72  

SBP^{e} (mm Hg), median (IQR)  112.00 (103.75121.25)  112.00 (105.00126.50)  112.00 (102.75118.75)  .92  

DBP^{f} (mm Hg), mean (SD)  74.11 (11.11)  72.95 (14.24)  75.00 (8.12)  .54  



RBC^{g} (10^{–9}/L), median (IQR)  4.51 (4.304.95)  4.40 (4.254.89)  4.71 (4.335.08)  .19  

HGB^{h} (g/L), mean (SD)  131.59 (10.03)  128.85 (11.45)  133.69 (8.42)  .11  

HCT^{i} (%), mean (SD)  44.10 (4.32)  43.31 (4.28)  44.70 (4.34)  .28  

MCV^{j} (fL), median (IQR)  94.10 (90.9096.60)  94.35 (96.5096.58)  94.00 (91.7396.78)  .89  

MCH^{k} (pg), median (IQR)  28.77 (27.4629.82)  28.54 (27.1829.77)  28.82 (27.5829.90)  .71  

MCHC^{l} (g/L), mean (SD)  304.62 (15.21)  304.46 (14.72)  304.75 (15.86)  .95  

RDWCV^{m} (%), median (IQR)  13.10 (12.3014.83)  14.25 (12.7521.03)  12.70 (12.2513.53)  .02  

RDWSD^{n} (fL), median (IQR)  44.40 (41.4846.68)  44.40 (41.0046.83)  44.55 (41.4846.70)  .84  



VO_{2}maxCPET^{o} (mL·kg^{–1}·min^{–1}), mean (SD)  30.17 (5.01)  27.80 (4.55)  32.00 (4.64)  .004  

VO_{2}maxSWT^{p} (mL·kg^{–1}·min^{–1}), median (IQR)  30.50 (27.7534.25)  28.00 (25.2532.00)  32.00 (30.0037.00)  .001 
^{a}AMS: acute mountain sickness.
^{b}Differences were considered statistically significant if
^{c}HR: heart rate.
^{d}SpO_{2}: oxygen saturation.
^{e}SBP: systolic blood pressure.
^{f}DBP: diastolic blood pressure.
^{g}RBC: red blood cell.
^{h}HGB: hemoglobin.
^{i}HCT: hematocrit.
^{j}MCV: mean corpuscular volume.
^{k}MCH: mean corpuscular hemoglobin.
^{l}MCHC: mean corpuscular hemoglobin concentration.
^{m}RDWCV: red blood cell distribution widthcoefficient of variation.
^{n}RDWSD: red blood cell distribution widthstandard deviation.
^{o}VO_{2}maxCPET: maximum oxygen consumption measured by cardiopulmonary exercise test.
^{p}VO_{2}maxSWT: maximum oxygen consumption estimated by smartwatch test.
Correlations and differences between the estimated maximum oxygen consumption in the smartwatch test and the measured maximum oxygen consumption in the cardiopulmonary exercise test.

VO_{2}maxCPET^{a} (mL·kg^{–1}·min^{–1}), mean (SD)  VO_{2}maxSWT^{b} (mL·kg^{–1}·min^{–1}), mean (SD)  CE^{c} (mL·kg^{–1}·min^{–1}), mean (SD) 

Intraclass correlation 
Mean absolute error (mL·kg^{–1}·min^{–1})  Mean absolute percentage 

Low 
30.17 (5.01)  31.28 (5.17)  1.11 (1.73)  4.35 (45) ( 
0.943 ( 
0.942 ( 
1.761  6 
High 
25.20 (6.46)  26.17 (6.71)  0.98 (1.54)  4.05 (40) ( 
0.973 ( 
0.973 ( 
1.610  6.80 
^{a}VO_{2}maxCPET: maximum oxygen consumption measured by the cardiopulmonary exercise test.
^{b}VO_{2}maxSWT: maximum oxygen consumption estimated by the smartwatch test.
^{c}CE: constant error (arithmetic mean of the difference between estimated and measured VO_{2}max).
^{d}Differences were considered statistically significant if
Linear regression plots between the estimated maximum oxygen consumption measured by smartwatch test and maximum oxygen consumption measured by cardiopulmonary exercise testing. Pearson correlation between the maximum oxygen consumption estimated by smartwatch and measured by cardiopulmonary exercise testing at low altitude (A) and at high altitude (B). The coefficient of determination (R2) and 95% CI bounds (dotted line) are depicted for the regression lines (solid). VO_{2}maxCPET: maximum oxygen consumption measured by cardiopulmonary exercise testing; VO_{2}maxSWT: estimated maximum oxygen consumption by smartwatch test.
BlandAltman plots between the estimated maximum oxygen consumption by smartwatch test and maximum oxygen consumption measured by cardiopulmonary exercise test at low altitude (A) and at high altitude (B). Mean biases (solid line), 95% limits of agreement (dashed line), and equality (dotted line) are also depicted. VO_{2}maxCPET: maximum oxygen consumption measured by cardiopulmonary exercise test; VO_{2}maxSWT: estimated maximum oxygen consumption by smartwatch test.
There was a significant difference in the VO_{2}max values at low altitude between the participants with and without AMS. VO_{2}maxCPET in the AMS group was lower than that in the nonAMS group (27.80 [SD 4.55] vs 32.00 [SD 4.64], respectively;
(A) Distribution of the estimated maximum oxygen consumption measured by smartwatch test and cardiopulmonary exercise test based on the diagnosis of acute mountain sickness. (B) Diagram of the probability of acute mountain sickness occurrence for different ranges of the maximum oxygen consumption value at low altitude (blue: maximum oxygen consumption measured by cardiopulmonary exercise test; orange: maximum oxygen consumption measured by smartwatch test). **Significantly different between acute mountain sickness and non–acute mountain sickness at
To further explore the association between VO_{2}max and AMS, a univariate analysis was performed.
Binomial logistic regression analysis of factors related to acute mountain sickness.
Variables  Univariable  Multivariable  Multivariable  

OR^{a} (95% CI)  OR (95% CI)  OR (95% CI)  
Age (years)  1.016 (0.9421.096)  .69  N/A^{c}  N/A  N/A  N/A 
Male (Y/N^{d})  2.333 (0.6847.960)  .18  N/A  N/A  N/A  N/A 
BMI (kg/m^{2})  1.037 (0.8521.262)  .72  N/A  N/A  N/A  N/A 
Tobacco (Y/N)  1.636 (0.2689.980)  .59  N/A  N/A  N/A  N/A 
Alcohol (Y/N)  4.000 (0.74421.496)  .11  N/A  N/A  N/A  N/A 
HR^{e} (beats/min)  1.048 (0.9821.118)  .16  N/A  N/A  N/A  N/A 
SpO_{2}^{f} (%)  0.907 (0.5581.472)  .69  N/A  N/A  N/A  N/A 
SBP^{g} (mm Hg)  1.002 (0.9651.040)  .91  N/A  N/A  N/A  N/A 
DBP^{h} (mm Hg)  0.983 (0.9321.037)  .53  N/A  N/A  N/A  N/A 
VO_{2}maxCPET^{i} (mL·kg^{1}·min^{1})  0.807 (0.6860.949)  .01  0.770 (0.6400.926)  .006  N/A  N/A 
VO_{2}maxSWT^{j} (mL·kg^{–1}·min^{–1})  0.765 (0.6350.922)  .005  N/A  N/A  0.720 (0.5780.898)  .004 
RBC^{k} (10^{–9}/L)  0.711 (0.2192.308)  .57  N/A  N/A  N/A  N/A 
HGB^{l} (g/L)  0.949 (0.8891.012)  .11  N/A  N/A  N/A  N/A 
HCT^{m} (%)  0.923 (0.8001.066)  .28  N/A  N/A  N/A  N/A 
MCV^{n} (fL)  0.966 (0.8761.064)  .48  N/A  N/A  N/A  N/A 
MCH^{o} (pg)  0.892 (0.6601.205)  .46  N/A  N/A  N/A  N/A 
MCHC^{p} (g/L)  0.999 (0.9611.038)  .95  N/A  N/A  N/A  N/A 
RDWCV^{q} (%)  1.177 (0.9991.386)  .05  1.263 (1.0281.553)  .03  1.273 (1.0271.577)  .03 
RDWSD^{r} (fL)  0.985 (0.8501.141)  .84  N/A  N/A  N/A  N/A 
^{a}OR: odds ratio.
^{b}Differences were considered statistically significant if
^{c}N/A: not applicable.
^{d}Y/N: yes/no.
^{e}HR: heart rate.
^{f}SpO_{2}: oxygen saturation.
^{g}SBP: systolic blood pressure.
^{h}DBP: diastolic blood pressure.
^{i}VO_{2}maxCPET: maximum oxygen consumption measured by cardiopulmonary exercise test.
^{j}VO_{2}maxSWT: maximum oxygen consumption estimated by smartwatch test.
^{k}RBC: red blood cell.
^{l}HGB: hemoglobin.
^{m}HCT: hematocrit.
^{n}MCV: mean corpuscular volume.
^{o}MCH: mean corpuscular hemoglobin.
^{p}MCHC: mean corpuscular hemoglobin concentration.
^{q}RDWCV: red blood cell distribution widthcoefficient of variation.
^{r}RDWSD: red blood cell distribution widthstandard deviation.
As both VO_{2}max and RDWCV were closely related to AMS, we constructed the combined predictive models for AMS.
Either the AUC of the VO_{2}maxCPET or VO_{2}maxSWT was higher than that of RDWCV (both
Receiver operating characteristic curves to assess the performance of the maximum oxygen consumption measured by cardiopulmonary exercise test and the maximum oxygen consumption estimated by smartwatch test in predicting acute mountain sickness.^{a}

AUC^{b} (95% CI)  Optimal cutoff 
Sensitivity (%)  Specificity (%)  PPV^{c} (%)  NPV^{d} (%) 
VO_{2}maxCPET^{e}  0.743 (0.5970.889)  26.50  45  96.15  90  69.44 
VO_{2}maxSWT^{f}  0.785 (0.6460.923)  29.50  65  88.46  81.25  76.67 
RDWCV^{g}  0.708 (0.5470.868)  13.10  75  69.23  65.22  78.26 
Model 1: VO_{2}maxCPET + RDWCV  0.804 (0.6750.933)  N/A^{h}  65  92.31  87.50  77.42 
Model 2: VO_{2}maxSWT + RDWCV  0.839 (0.7200.959)  N/A  80  84.62  80  84.62 
^{a}Comparison of area under the curve: maximum oxygen consumption measured by cardiopulmonary exercise test versus maximum oxygen consumption estimated by smartwatch test (
^{b}AUC: area under the curve.
^{c}PPV: positive predictive value.
^{d}NPV: negative predictive value.
^{e}VO_{2}maxCPET: maximum oxygen consumption measured by cardiopulmonary exercise test.
^{f}VO_{2}maxSWT: maximum oxygen consumption estimated by smartwatch test.
^{g}RDWCV: red blood cell distribution widthcoefficient of variation.
^{h}N/A: not applicable.
Receiver operating characteristic curves for maximum oxygen consumption measured by the cardiopulmonary exercise test (blue solid line), estimated maximum oxygen consumption by the smartwatch test (green solid line), and red blood cell distribution widthcoefficient of variation (red solid line), and for Model 1 (blue dotted line: combination of maximum oxygen consumption measured by cardiopulmonary exercise test and red blood cell distribution widthcoefficient of variation) and Model 2 (green dotted line: combination of estimated maximum oxygen consumption by smartwatch test and red blood cell distribution widthcoefficient of variation) in predicting acute mountain sickness. VO_{2}maxCPET: maximum oxygen consumption measured by cardiopulmonary exercise test; VO_{2}maxSWT: estimated maximum oxygen consumption by smartwatch test; RDWCV: red blood cell distribution widthcoefficient of variation.
Our study comparatively evaluated the VO_{2}max (CPET vs SWT) of individuals at a low altitude and subsequently at a high altitude. We demonstrated that the smartwatch device was a feasible and accurate tool for assessing cardiorespiratory fitness at both altitudes. We also proposed a novel model based on smartwatchderived VO_{2}max with good performance in predicting AMS. Our easytouse approach for estimating VO_{2}max can be more widely applied for screening individuals susceptible to AMS on a large scale.
Previous clinical trials [
Similar to that shown in a previous report, VO_{2}max was lower by approximately 16.5% at 3900 m evaluated by both CPET and SWT compared to that at low altitude in our trial, which can be attributed to the reduction of atmospheric PO_{2} at high altitude [
VO_{2}max evaluation using CPET is inconvenient in practice. In the past few decades, several new methods for estimating VO_{2}max have been investigated through a submaximal exercise protocol, including the Queen college step test [
VO_{2}max represents the maximum oxygen utilization capacity of an individual. In normoxic conditions, a higher VO_{2}max indicates greater exercise capacity and better cardiorespiratory fitness [
It can be concluded from our results that individuals with a higher VO_{2}max are unlikely to develop AMS. ROC analysis demonstrated that VO_{2}maxCPET and VO_{2}maxSWT showed a similar predictive value, particularly for VO_{2}maxSWT, with a specificity up to 88.46% for a cutoff value of 29.5 mL·kg^{–1}·min^{–1}. The high specificity ensures a low incidence of AMS when VO_{2}max is below the cutoff value of lowlanders unsuitable for acute highaltitude exposure. In addition, we found that RDWCV was more closely related to AMS than other routine blood parameters. We believe that the low RDWCV represents a uniform distribution of erythrocyte developmental states, indicating a more effective compensation response of RBC under acute hypoxia stress [
The VO_{2}max estimated by SWT and measured by CPET has high consistency, indicating that smartwatches may replace the CPET system to obtain VO_{2}max accurately and objectively by monitoring the common physical activities with a portable, lowcost system. After each exercise, the smartwatch can measure and record the exercise information, integrate the calculation, and update the VO_{2}max value. In addition, VO_{2}max measured at low altitudes is highly correlated with the occurrence of AMS, with satisfactory prediction performance. Therefore, it is feasible to use a smartwatch to measure VO_{2}max at low altitudes to evaluate the possibility of AMS. In the future, this will benefit tourists, temporary workers, and other individuals who plan to travel at high altitudes and will help in identifying participants susceptible to AMS before highaltitude exposure.
To advance this field, several measures are required. First, there is an urgent need for validation standards for smartwatch devices to enable standardized research. Second, the open disclosure of commercial validation studies can enable better resource usage, as studies will not have to be repeated unnecessarily. Third, further development of smartwatch devices will allow new possibilities in the field of VO_{2}max monitoring. Finally, subsequent trials should continue to focus on validating these devices compared to conventional standards and broaden their use and demonstrate new possibilities for accurate VO_{2}max monitoring.
This study had some limitations. Notably, the Lake Louise consensus scoring system (2018 version) is subjective; therefore, we described each symptom as clearly as possible and provided necessary instructions before the participants completed the questionnaire to deal with the subjectivity. Second, running exercise instead of cycling should be implemented by CPET to minimize the inconsistencies in VO_{2}max with SWT, which was not applied here due to the great safety risk at high altitude. Further studies and repeated measures are required to develop and investigate the predictive models of the SWT method based on submaximal running programs in terms of validity and reliability [
Our findings demonstrate that VO_{2}max estimated by SWT and CPET have good accuracy and agreement at both low and high altitudes. Importantly, smartwatchbased VO_{2}max at low altitudes was a convenient and effective approach to predict AMS and to identify susceptible individuals following acute highaltitude exposure, particularly by combining the RDWCV at low altitudes.
Original data of the cardiopulmonary exercise test and smartwatch test in this study.
acute mountain sickness
area under the curve
cardiopulmonary exercise test
Firstbeat fitness test
mean absolute percentage error
odds ratio
red blood cell
red blood cell distribution widthcoefficient of variation
receiver operating characteristic
oxygen saturation
smartwatch test
maximum oxygen consumption
We appreciate all the volunteers in this clinical trial and the Shigatse hospital in Tibet. This study was supported by grants from the National Natural Science Foundation of China (81730054) and research project of People's Liberation Army (BLJ18J007).
The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.
None declared.