• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1147-1155
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• 2013

In this study, we designed and implemented a step detection analyzer that can compare and analyze the step detection rates and results among the step detection algorithms. The step detection analyzer converts 3-axes accelerometer data into continuous energy stream through SVM operation, shows the horizontal comparison among the step detection results for each step detection algorithms, and can make elemental detection analyses. For these processes, the step detection analyzer presents the continuous energy stream as energy waveform, checks the peak values and time location of the detected steps with step detection algorithms, and gives visual interface to get some possible causes in cases of step detection miss. It can also give the threshold graph for each algorithm to check the threshold value on missed cases directly and can help to get more appropriate threshold values or other adjustable parameters in step detection algorithm. This step detection analyzer can be applied efficiently on performance enhancement of step detection algorithm, on deciding an appropriate algorithm for a specific step counter system in the various step counter filed operations.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.257-264
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• 2013

In this study, we have designed the variable amplitude threshold algorithm that can enhance the accuracy of step count using variable amplitude. This algorithm converts the x, y, z sensor values into a single energy value($E_t$) by using SVM(Signal Vector Magnitude) algorithm and can pick step count out over 99% of accuracy through the peak data detection algorithm and fixed peak threshold. To prove the results, We made the noise filtering with the fixed amplitude threshold from the amplitude of energy value that found out the detection error was increasing, and it's the key idea of the variable amplitude threshold that can be adapted on the continuous data evaluation. The experiment results shows that the variable amplitude threshold algorithm can improve the average step count accuracy up to 98.9% at 10 Hz sampling rate and 99.6% at 20Hz sampling rate.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.2
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• pp.57-64
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• 2015

At the case of peak threshold algorithm, 3-axes data should sample step data over 20 Hz to get sufficient accuracy. But most of the digital sensors like 3-axes accelerometer have very low sampling rate caused by low data communication speed on limited SPI or $I^2C$ bandwidth of the low-cost MPU for ubiquitous devices. If the data transfer rate of the 3-axes accelerometer is getting slow, the sampling rate also slows down and it finally degrades the data accuracy. In this study, we proved there is a distinct functional relation between the sampling rate and threshold on the peak threshold step detection algorithm under the 20Hz frequency, and made a threshold function through the experiments. As a result of experiments, when we apply threshold value from the threshold function instead of fixed threshold value, the step detection error rate can be lessen about 1.2% or under. Therefore, we can suggest a peak threshold based new step detection algorithm with threshold function and it can enhance the accuracy of step detection and step count. This algorithm not only can be applied on a digital step counter design, but also can be adopted any other low-cost ubiquitous sensor devices subjected on low sampling rate.

• Smart Media Journal
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• v.4 no.2
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• pp.68-76
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• 2015

Recently, research on indoor locating techniques using smart device sensors has been conducted actively, Owing to the exponential increase in the use of various smart devices. However, in order to develop indoor location techniques, there are limitations due to the requirement that the tracking system has to function without GPS. In this paper, we propose an accurate indoor locating system that does not require additional infrastructure. The proposed scheme is developed based on the idea that the advantages and disadvantages of "Wi-Fi Fingerprinting" and "Step Detection" techniques are complementary. In the proposed scheme, we track users with "Step Detection," and correct errors with "Wi-Fi Fingerprinting." In this paper, we demonstrate the effectiveness and feasibility of our proposed scheme through experiments.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.176-178
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• 2016

본 논문은 손목에 착용한 3축 가속도계 신호로부터 걷기, 달리기 상태일 때 걸음 수를 검출하는 방법을 제안한다. 성인 남자 4명의 피 실험자를 대상으로 트레드밀에서 2km/h, 4km/h, 6km/h, 8km/h의 속도로 신호를 수집하였다. 3축 가속도 신호에서 SMV를 계산한 후 Moving Max를 적용한 후 Vally Detection을 하여 걸음 수를 검출하였다. 약 2300보의 수집 신호에서 약 97.77%의 인식 결과를 도출하였다.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.93-94
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• 2007

노약자 활동상황 감시에서 활동정보와 위치정보는 매우 중요하다. 본 논문에서는 3축 가속도센서와 ZigBee 통신을 이용하여 노약자 활동상황 감시를 위한 시스템을 개발하였다. 가속도센서로부터 활동량을 측정하고 운동량을 계산하기 위한 걸음 검출을 하며, ZigBee 통신을 이용하여 감시시스템으로 전송하여 실시간으로 노약자의 활동상황을 모니터링 할 수 있다. 추가로 부착위치에 강인한 걸음 검출 알고리즘을 제안하였으며, 실제 실험을 통해 가속도센서를 가슴에 부착할 경우 99.83%의 정확도로 걸음을 검출할 수 있음을 확인하였다. 또한 ZigBee 통신의 수신신호세기를 이용하여 노약자가 있는 방을 구별할 수 있었다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.411-412
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• 2012

본 논문에서는 인간의 가장 기본적이며 기초적인 운동인 걸음걸이로부터 검출할 수 있는 걸음 수 및 보행분석을 위해 전도성 섬유를 이용한 전기용량성압력 센서를 깔창형태로 개발하였다. 개발된 깔창 형태의 센서는 보행시의 압력을 측정하여 보행신호를 검출하고, 검출된 신호를 이용하여 걸음 수 및 보행 분석을 실시하였다. 개발된 센서의 성능 검증을 위하여 상용 만보계 및 관찰자의 수계로 도출된 보수를 비교하였으며, 자세에 따른 압력차이를 측정하였다. 기존의 상용 만보계는 저속(1 Km/h)으로 걸었을 때 보수가 잘 측정되지 않은 반면 개발된 센서는 저속에서도 관찰자 수계대비 정확한 보수를 도출 할 수 있었다. 또한 자세에 따라 압력 값을 토대로 사용자의 자세를 모니터링 할 수 있음을 보였다. 본 연구는 향후 스마트폰과 무선 연동하는 스마트 보행관리 시스템을 개발하기 위한 기초연구이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.731-734
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• 2013

치매 환자들은 안전한 생활과 건강한 삶을 위해 행동 정보에 대한 모니터링이 필요하다. 이러한 서비스를 위해 휴대가 간편하면서 항상 착용 가능한 모니터링 도구가 필요하며, 기억과 인지장애로 인한 배회 활동과 넘어짐과 같은 응급상황에 빠르게 대처하기 위한 다양한 센서기술의 적용이 필수적이다. 따라서 본 논문에서는 현재 개발 중인 치매환자를 위한 시계형 장치(스마트 시계)와 서버시스템의 구조 및 기능에 대해서 서술하면서, 3 축 가속도 센서 기반의 개선된 걸음 수 검출 알고리즘을 제안한다. 개선된 걸음 수 검출 알고리즘은 일반적인 걸음 수를 96%의 정확도로 검출함을 확인했다.

• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.17-26
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• 2011

We have developed a wearable device that can convert sensor data into real-time step counts. Sensor data on gait were acquired using a triaxial accelerometer. A test was performed according to a test protocol for different walking speeds, e.g., slow walking, walking, fast walking, slow running, running, and fast running. Each test was carried out for 36 min on a treadmill with the participant wearing an Actical device, and the device developed in this study. The signal vector magnitude (SVM) was used to process the X, Y, and Z values output by the triaxial accelerometer into one representative value. In addition, for accurate step-count detection, we used three algorithms: an heuristic algorithm (HA), the adaptive threshold algorithm (ATA), and the adaptive locking period algorithm (ALPA). The recognition rate of our algorithm was 97.34% better than that of the Actical device(91.74%) by 5.6%.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.3
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• pp.245-250
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• 2015

Portable devices, such as smart phones and personal digital assistants (PDAs) play an important role in our everyday life. In this paper, we propose a step count algorithm based on SVM(signal vector magnitude) and a adaptive threshold processing to monitor the physical activity. The algorithm measures a user's step counts using the smart phone's inbuilt accelerometer and g sensor. Experiment results showed the proposed algorithm has good performance in accuracy and adaptability than the app on your smart phone.