• Safety and Health at Work
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• v.4 no.1
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• pp.46-51
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• 2013

Objectives: Load carrying tasks are recognized as one of the primary occupational factors leading to slip and fall injuries. Nevertheless, the mechanisms associated with load carrying and walking stability remain illusive. The objective of the current study was to apply local dynamic stability measure in walking while carrying a load, and to investigate the possible adaptive gait stability changes. Methods: Current study involved 25 young adults in a biomechanics research laboratory. One tri-axial accelerometer was used to measure three-dimensional low back acceleration during continuous treadmill walking. Local dynamic stability was quantified by the maximum Lyapunov exponent (maxLE) from a nonlinear dynamics approach. Results: Long term maxLE was found to be significant higher under load condition than no-load condition in all three reference axes, indicating the declined local dynamic stability associated with load carrying. Conclusion: Current study confirmed the sensitivity of local dynamic stability measure in load carrying situation. It was concluded that load carrying tasks were associated with declined local dynamic stability, which may result in increased risk of fall accident. This finding has implications in preventing fall accidents associated with occupational load carrying.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.703-706
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• 2007

The real-time monitoring about the activity of the human provides useful information about the activity quantity and an ability. This study developed a system for human physical activity assessment in ambulatory monitoring using portable sensing device combining a tri-axial accelerometer and wireless sensor node. This real-time system is able to identify several postures, posture transitions and movements with classification algorithm. In addition, this system also features fall detection capability. The results of the assessment for evaluating the performance of the system show high identification accuracy.

• Journal of the Korean Society of Physical Medicine
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• v.13 no.3
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• pp.19-25
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• 2018

PURPOSE: Most gait assessment tools are expensive and require controlled laboratory environments. Tri-axial accelerometers have been used in gait analysis as an alternative to laboratory assessments. Many smartphones have added an accelerometer, making it possible to assess spatio-temporal gait parameters. This study was conducted to confirm the reliability and validity of a smartphone-based accelerometer at quantifying spatio-temporal gait parameters of stroke patients when attached to the body. METHODS: We measured gait parameters using a smartphone accelerometer and gait parameters through the GAITRite analysis system and the reliability and validity of the smartphone-based accelerometer for quantifying spatio-temporal gait parameters for stroke patients were then evaluated. Thirty stroke patients were asked to walk at self-selected comfortable speeds over a 10 m walkway, during which time gait velocity, cadence and step length were computed from smartphone-based accelerometers and validated with a GAITRite analysis system. RESULTS: Smartphone data was found to have excellent reliability ($ICC2,1{\geq}.98$) for measuring the tested parameters, with a high correlation being observed between smartphone-based gait parameters and GAITRite analysis system-based gait parameters (r = .99, .97, .41 for gait velocity, cadence, step length, respectively). CONCLUSION: The results suggest that specific opportunities exist for smartphone-based gait assessment as an alternative to conventional gait assessment. Moreover, smartphone-based gait assessment can provide objective information about changes in the spatio-temporal gait parameters of stroke subjects.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.495-496
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• 2013

본 논문에서는 패치형 3축 가속도 센서와 스마트 디바이스를 활용하여 유산소 운동에 따라 가속도 센서를 통해 얻은 데이터의 특징을 분석하고 유산소 운동을 분류하는 모바일 시스템을 설계하였다. 제안하는 시스템을 이용하여 사용자가 하고 있는 유산소 운동을 스마트 디바이스에서 실시간으로 분류하고 분류된 운동에 따라 운동 횟수와 사용자의 움직임을 분석하여 사용자에게 편의성과 운동 정보를 제공 할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1336-1339
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• 2009

산업화가 진행된 세계 주요 선진국들은 의학의 발달과 평균 수명의 증가로 고령화의 위기를 겪고 있다. 인구 고령화에 따라 치매 인구도 크게 증가하였다. 치매 인구의 증가는 국가와 가정의 물질적, 인적 비용을 증가시키고 있다. 이와 같은 사회문제를 해결하고 효율적인 치매 환자 관리를 위한 방법이 필요하다. 관찰 대상자가 치매 증상과 비슷하게 행동한다면 치매를 의심해 볼 수 있다. 본 논문에서는 3축 가속도 센서를 사용하여 대상자의 행위 정보를 수집하고 디지털화한다. 디지털화 된 행위정보를 치매 증상의 행동 패턴과 비교하여 관찰 대상자의 행동이 치매 증상인지 정상적인 활동인지 판단할 수 있는 방법을 소개한다.

• Korean Journal of Applied Biomechanics
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• v.19 no.1
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• pp.179-186
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• 2009

This works studied to compare gas analyzer with accelerometer and the estimation of energy expenditure based on different attaching position of tri-axial accelerometer such as waist and top of the foot Based on the fact that oxygen intake increases more radically linearly during walking more than 8.0km/hr. 9 male subjects performed walking and running on the treadmill with speed of $1.5{\sim}8.5km$/hr and $4.5{\sim}13.0km$/hr, respectively. Commercially available Nike + iPod Sports kit was used to compare energy expenditure with sensor module attached to their foot. Actual energy expenditure was determined by a continuous direct gas analyzer and two multiple regression equations of walking and running mode for different attaching position were developed. Results showed that estimation accuracy of energy expenditure using waist mounted accelerometer was higher than that of the top of the foot and Nike + iPod Sports kit. Results of energy expenditure based on waist and top of the foot showed that the crossover state of energy expenditure occurred at 7.5km/hr. But Nike + iPod Sports kit could not find intersection of energy expenditure in all nine subjects. Therefore the sensor module attached to the waist and separate multi regression equation by walking and running mode was the best to estimate more accurate prediction.

• Korean Journal of Applied Biomechanics
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• v.21 no.2
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• pp.253-258
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• 2011

The purpose of this study was to compare metabolic energy expenditure with the computed kinetic energy for different speeds of walking and running over the treadmill and to find the relevance for individual and group equation by performing a statistical analysis, Bland-Altman plot. Seven male subjects participated, and they were required to walk and run on the treadmill with the gas analyzer and triaxial accelerometer. Walking speeds were 3.0, 4.0, 5.0 and 6.0 km/h and running speeds were 7.0, 8.0 and 9.0 km/h respectively. Kinetic energy was calculated by the integration of acceleration data and compared with the metabolic energy measured by a gas analyzer. Correlation coefficients showed relatively good between the measured metabolic energy and the calculated kinetic energy. In addition, a dramatic increase in kinetic energy was also observed at the transition speed of walking and running, and two standard deviations in Bland-Altman plot, derived from the difference between measured and predicted values, were 1.14, 2.53, 2.93, 1.80, 2.80, 0.60 and 2.48 respectively. It was showed that there is no difference for methods of how to predict the kinetic energy expenditure for individual and group even though people had each different physical characteristic.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1557-1563
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• 2016

According to recent studies, poor sitting posture of the spine has been shown to lead to a variety of spinal disorders. For this reason, it is important to measure the sitting posture. We proposed a strategy for classification of sitting posture using machine learning. We retrieved acceleration data from single tri-axial accelerometer attached on the back of the subject's neck in 5-types of sitting posture. 6 subjects without any spinal disorder were participated in this experiment. Acceleration data were transformed to the feature vectors of principle component analysis. Support vector machine (SVM) and K-means clustering were used to classify sitting posture with the transformed feature vectors. To evaluate performance, we calculated the correct rate for each classification strategy. Although the correct rate of SVM in sitting back arch was lower than that of K-means clustering by 2.0%, SVM's correct rate was higher by 1.3%, 5.2%, 16.6%, 7.1% in a normal posture, sitting front arch, sitting cross-legged, sitting leaning right, respectively. In conclusion, the overall correction rates were 94.5% and 88.84% in SVM and K-means clustering respectively, which means that SVM have more advantage than K-means method for classification of sitting posture.

• 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%.

• The Journal of the Korean dental association
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• v.52 no.12
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• pp.734-743
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• 2014

Objectives: By introduced reciprocation motion file in dentistry, dentists benefit simple canal shaping procedure and time-saving. But, reciprocation motion generates uncomfortable vibration to doctors and patients. Because there was no study about this consideration, this study compared vibration pattern and power generated from reciprocation motion motor and conventional rotary motor. Materials & Methods: One conventional rotary motor; X-Smart (Dentsply Maillefer, Ballaigues, Switzerland); and two reciprocating motors; WaveOne Motor (Dentsply Maillefer, Ballaigues, Switzerland) and X-SMART PLUS (Dentsply Maillefer, Ballaigues, Switzerland); were used in this study. Triaxial $ICP^{(R)}$ Accelerometer (Model 356A12, PCB piezotronics, New York, USA) was attached on motor's handpiece head, and was measured tri-axial vibratory acceleration with NI Sound and Vibration Assistant 2009 software (National Instruments, Texas, USA). Mean vibratory acceleration and maximum vibratory acceleration was measured on fixed position and handed position. The results of vibratory acceleration were statistically analyzed using ANOVA and multiple comparisons are made using Turkey's test at p<0.05 level. Results: Reciprocating motors showed higher mean vibratory acceleration and maximum vibratory acceleration than conventional rotary motor (p<0.05). Between reciprocating motors, X-SMART PLUS had lower mean vibratory acceleration and maximum vibratory acceleration than WaveOne Motor (p<0.05). Conclusion: Reciprocating motors generate more vibration than conventional rotary motor. Further study about effect of vibration to dentist and patient is needed. And it seems to be necessary to make a standard about vibration level in endodontic motors.