• Journal of Life Science
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• v.19 no.10
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• pp.1368-1373
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• 2009

The purpose of this study was to assess the influence of waist size on the reliability and validity of pedometers to count steps in children and youth. The participants for this study were 20 children and youth, composed of 14 Hispanic and 6 Caucasian children. Ten children and youth had waist circumferences greater than the $85^{th}$ percentile (Body Mass Index (BMI)=$28.91\pm3.07$), and 10 children and youth had waist circumferences smaller than the $50^{th}$ percentile (BMI=$18.05\pm1.55$). To examine pedometer reliability, each child completed 3 ascent and descent trials up a set of 15 stairs while wearing a Yamax SW-701 pedometer. The main effect of trials was not statistically significant for the stair ascent trials F (2, 36)=2.575 or for the descent trials F (2, 36)=0.235. The trial by group interaction was also not statistically significant. To examine the influence of waist circumference on the validity of the pedometer in counting walking steps at a self-selected walking pace, the children and youth in the two groups completed a 400-m course. The main effect on the groups was statistically significant, F (1, 18)=7.489. The main effect of counting techniques was not statistically significant, F (1, 18)=2.983 (hand-counted vs. pedometer counted). Overall, the trial and trial by group interaction comparisons for the 400-m walk were not statistically significant, suggesting that the pedometer was equally valid as a tool for assessing walking steps in high waist circumference (HWC) and low waist circumference (LWC) in children and youth.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1150-1158
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• 2010

In this paper, a new reliable portable activity monitoring device implemented with the buddhist-style bowing activity and walking step detection algorithm, is presented. In order to monitor the bowing and walking activities, miniaturized 3-axis accelerometer sensor with the sensitivity of 800 mV/g was used. After initial signal conditioning, vector magnitude of accelerometer signals was calculated. Syntactic peak detection method was used in order to feature points. All signal processing algorithms were implemented in ultra-low power microcontroller MSP430 with double precision floating point arithmetic. For evaluation, 19 young man($24.22\pm5.22$ yrs) and woman($22.28\pm2.72$ yrs) were involved. The accuracy of the proposed algorithms were 98.91 %($\pm0.011$) for walking step detection and 98.25 %($\pm0.023$) for buddhist-style bowing activity. Comparing to the commercialized pedometer accuracy, 87.1 %($\pm0.058$), the proposed walking step detection algorithms show more reliable accuracy.

• Design Convergence Study
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• v.16 no.6
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• pp.123-135
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• 2017

In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.

• Journal of muscle and joint health
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• v.29 no.2
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• pp.91-99
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• 2022

Purpose: The purpose of this study was to examine the level of agreement between smartphone apps and self-reported physical activity questionnaires. Methods: Quantitative methods were used to assess the correlation and agreement between the number of steps counted by a smartphone app and the amount of walking reported in a survey. A total of 29 adults who used smartphones were recruited from a university, and their step counts from their smartphone pedometers and responses to the international physical activity questionnaire (IPAQ) were collected over a 10-week period. Results: An analysis of 170 data pairs with Spearman's rho correlation and a Bland-Altman plot revealed a positive correlation between step counts from the smartphone app and walking activity from the IPAQ. The Bland-Altman plot also demonstrated the agreement to be improved among female participants. Conclusion: In assessing walking activity, smartphone pedometer apps showed good correlation with the IPAQ and improved agreement with the IPAQ among women. Therefore, it is suggested that the participants' gender and activity intensity, as well as the accuracy of measurement tools, should be considered in an evaluation of the delivery of physical activity promotion programs through smartphone apps.

• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.516-520
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• 2009

The purpose of this study is to determine optimal filtering condition and threshold for the detection of gait-cycles for various walkway slopes as well as gait velocities. Ten young healthy subjects with accelerometer system on thigh and ankle walked on a treadmill at 9 conditions (three speeds and three slopes) for 5 minutes. Two direction signals, i.e. anterior-posterior (AP) and superior-inferior (SI) directions, of each sensor (four sensor orientations) were used to detect specific events of gait cycle. Variation of the threshold (from -1G to 1G) and lowpass cutoff frequency (fc) were applied to the event detection and their performance was evaluated according to the error index (EI), which was defined as the combination of the accuracy and false positive rate. Optimal fc and threshold were determined for each slope in terms of the EI. The optimal fc, threshold and their corresponding EI depended much on the walkway slope so that their coefficients of variation (CV) ranged 19~120%. When all data for 3 slopes were used in the identification of optimal conditions for each sensor, the best error indices for all sensor orientations were comparable ranging 1.43~1.76%, but the optimal fc and threshold depended much on the sensor position. The result indicates that the gait-cycle detection robust to walkway slope is possible by threshold method with well-defined filtering condition and threshold.

• Journal of Korean Medicine for Obesity Research
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• v.13 no.2
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• pp.58-65
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• 2013

Objectives: The objective of this study was to analyse the methods being used to control food intake and physical activity in RCTs of human obesity. Methods: A total of 21 randomized controlled trials (RCTs) were investigated. Nine of which were domestic studies from "http://oasis.kiom.re.kr" and the other of which were foreign studies from systematic reviews of RCTs on herbal medicine for treatment of human obesity. Results: According to domestic studies, "low calorie diet" were recommended in five cases of the domestic studies, "maintain current dietary habit" were recommended in two and no information on diet was two. Considering the seven cases where the information on diet was available, patients' food intake were checked at every visit in six cases. Only two cases among the six had been dropped owing to the violation of dietary habit by patients. Exercises were prohibited in two cases, "maintain current level of phisical activity" were recommended in three cases and, from the rest, no information was available. The level of physical activity were not strictly controlled by any means hence no drop out. According to foreign studies, "low calorie diet" were recommended in two cases, "very low calorie diet (less than 700 kcal/day)" in one case, "maintain current dietary habit" in two cases, "do not eat fat" in two cases and no information was available in the rest five cases. Exercises which concerns spending about 300 kcal/day was recommended in one case, "moderate exercise" were recommended in three cases, "maintain current level of physical activity" were recommended in three cases and no information available in the rest five cases. Conclusions: In order to improve the accuracy of RCT, for the dietary side, researchers should record patient food intake at every visit by means of 24-hour dietary recall methods. This can be supplemented by multiple choice survey that are designed to help patients to diagnose themselves more accurately leading to less bias. For the exercise side, it is highly recommended to confine the exercises to walking only so as to quantify the amount of physical activity more easily by using pedometer.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.43-52
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• 2014

In this paper, we propose Gravity Removal and Vector Rotation algorithm for counting steps of wearable device, and we evaluated the proposed GRVR algorithm with Micro-Electro-Mechanical (MEMS) 3-axis accelerometer equipped in low-power wearable device while the device is mounted on various positions of a walking or running person. By applying low-pass filter, the gravity elements are canceled from acceleration on each axis of yaw, pitch and roll. In addition to DC-bias removal and the low-pass filtering, the proposed GRVR calculates acceleration only on the yaw-axis while a person is walking or running thus we count the step even if the wearable device's axis are rotated during walking or running. The experimental result shows 99.4% accuracies for the cases where the wearable device is mounted in the middle and on the right of the belt, and 91.1% accuracy which is more accurate than 83% of commercial 3-axis pedometer when worn on wrist for the case of axis-rotation.