• The Journal of Korean Physical Therapy
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• v.22 no.6
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• pp.59-63
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• 2010

Purpose: Driving a car is an essential component of daily life. For safe driving, each driver must perceive sensory information and respond rapidly and accurately. Brake response time (BRT) is a particularly important factor in the total stopping distance of a vehicle, and therefore is an important factor in traffic accident prevention research. The purpose of the current study was (1) to compare accelerometer. BRTs analyzed by three different methods and (2) to investigate possible correlations between accelerometer-BRTs and foot switch-BRTs, which are measured method using a foot switch. Methods: Eighteen healthy subjects participated in this study. BRT was measured with either a tri-axial accelerometer or a footswitch. BRT with a tri-axial accelerometer was analyzed using three methods: maximum acceleration time, geometrical center, and center of maximum and minimum acceleration values. Results: Both foot switch-BRTs and accelerometer-BRTs were delayed. ANOVA for accelerometer BRTs yielded significant main effects for axis and analysis, while the interaction effect between axis and analysis was not significant. Calculating the Pearson correlation between accelerometer-BRT and foot switch-BRT, we found that maximum acceleration time and center of maximum and minimum acceleration values were significantly correlated with foot switch-BRT (p<0.05). The X axis of the geometrical center was significantly correlated with foot switch-BRTs (p<0.05), but Y and Z axes were not (p>0.05). Conclusion: These findings suggest that the maximum acceleration time and the center of maximum and minimum acceleration value are significantly correlated with foot switch-BRTs.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.506-513
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• 2014

In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.7
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• pp.1068-1079
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• 2008

Tilt and heading angles information of a remotely operated vehicle (ROV) are very important in underwater navigation. This paper presents a low.cost tilt and heading estimation system. Three single.axis rate gyros, a tri-axis accelerometer, and a tri-axis magnetometer are used. Output signals coming from these sensors are fused by two Kalman filters. The first Kalman filter is used to estimate roll and pitch angles and the other is for heading angle estimation. By using this method, we have obtained tilt (roll and pitch angles) and heading information which are reliable over long period of time. Results from experiments have shown the performance of the presented system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.481-484
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• 2008

Sudden infant death syndrome (SIDS) is the leading cause of unexplained death of an apparently healthy infant aged one month to one year. This paper presents a infant monitoring system which detects the movement of infants to prevent SIDS. The proposed system is composed of an movement sensing part and a motion detecting part. The movement sensing part uses a tri-axis accelerometer. The motion detecting part is based on the LVQ algorithm. The proposed monitoring system connects to an alarm for alerting a parent when an infant is in a predetermined position. We evaluated the performance of the monitoring system through experiments.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.103-111
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• 2011

The research has increased the role of physical activity in promoting health and preventing chronic disease. Estimating algorithm of physical activity energy expenditure was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). COUNT method has been proven through experiments of validity Freedson, Hendelman, Leenders, Yngve was implemented by applying the SVM method. A total of 10 participants(5 males and 5 females aged between 20 and 30 years). The activity protocol consisted of three types on treadmill; participants performed three treadmill activity at three speeds(3, 5, 8 km/h). These activities were repeated four weeks. Customized estimating algorithm for energy expenditure of physical activities were implemented with COUNT and SVM correlation between the data.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.27-33
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• 2011

Estimating algorithm of physical activity energy expenditure and physical activity intensity was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). A total of 10 participants(5 males and 5 females aged between 20 and 30 years). The ActiGraph(LLC, USA) and Fitmeter(Fit.life, korea) was positioned anterior superior iliac spine on the body. The activity protocol consisted of three types on treadmill; participants performed three treadmill activity at three speeds(3, 5, 8 km/h). Each activity was performed for 7 minutes with 4 minutes rest between each activity for the steady state. These activities were repeated four weeks. Algorithm for METs, kcal and intensity of activities were implemented with ActiGraph and Fitmeter correlation between the data.

• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.87-93
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• 2012

The purpose of this study suggests a personalized algorithm of physical activity energy expenditure prediction through comparison and analysis of individual physical activity. The research for a 3-axial accelerometer sensor has increased the role of physical activity in promoting health and preventing chronic disease has long been established. Estimating algorithm of physical activity energy expenditure was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). A total of 10 participants(5 males and 5 females aged between 20 and 30 years). The activities protocol consisted of three types on treadmill; participants performed three treadmill activity at three speeds(3, 5, 8 km/h). These activities were repeated four weeks.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.1
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• pp.1-8
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• 2012

Estimating algorithm of physical activity energy expenditure was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). A total of 33 participants(15 males and 18 females) that performed walking and running on treadmill at 2 ~ 11 km/h speeds(each stage increase 1km/h). Algorithm for energy expenditure of physical activities were implemented with $VO_2$ consumption and SVM correlation between the data. Algorithm consists of three kinds and hip, wrist, waist and hip can be used to apply.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1675-1681
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• 2008

Sudden infant death syndrome (SIDS) is the leading cause of unexplained death of an apparently healthy infant aged one month to one year. This paper presents an infant monitoring system which detects the movement of infants to prevent SIDS. The proposed system is composed of a movement tenting part and a motion detecting part. The movement sensing part uses a tri-axis accelerometer. The motion detecting part is based on the LVQ algorithm. The proposed monitoring system connects to an alarm for alerting a parent when an infant is in a predetermined position. We evaluated the performance of the monitoring system through experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.265-269
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• 2008

Home health care with compact wearable units sounds to be a convenient solution for the elderly people living independently. This paper presents a method to detect fall from the other activities of daily living and also to classify those activities. This kind of ambulatory monitoring enables them to get an emergency help in the case of the fatal fall event and can provide their general health status by observing the activities being performed in daily life. A tri-axial accelerometer sensor is used to get the acceleration anomalies associated with the user's movements. The three axis acceleration data are transferred to the base station sensor node via an IEEE 802.15.4 compliant zigbee module. The base station sensor node sends the data to base station PC for an offline processing. This work shows the feature set preparation using the principal component analysis (PCA) for the designing of neural network. The work includes the most common activities of daily living (ADL) like Rest, Walk and Run along with the detection of fall events from ADL. The angle from the vertical is found to be the most significant feature parameter for classification of fall while mean, standard deviation and FFT coefficients were used as the feature parameter for classifying the other activities under consideration. The accuracy for detection of fall events is 86%. The overall accuracy for ADL and fall is 94%.