• Title, Summary, Keyword: Spatio-temporal parameters

Search Result 76, Processing Time 0.033 seconds

A Study on the Characteristics of Gait in Patients with Chronic Low Back Pain (만성요통환자의 보행특성에 관한 연구)

  • Kim, Kyoung;Ko, Joo-Yeon;Lee, Sung-Young
    • The Journal of Korean Physical Therapy
    • /
    • v.21 no.2
    • /
    • pp.79-85
    • /
    • 2009
  • Purpose: This study examined the characteristics of gait in patients with chronic low back pain. Methods: The subjects were out-patients suffering from chronic low back pain at the department of physical therapy, B hospital in Seoul. Gait analysis was performed by dividing the subjects into two groups. The study and control group comprised 15 chronic low back pain patients and 14 healthy people, respectively. Gait analysis was performed using a VICON 512 Motion Analysis System to obtain the spatio-temporal and kinematic parameters. Results: First, there was a significant difference in the spatio-temporal parameters between the two groups (p<0.05). Second, the study group showed significant differences in the kinematic parameters during the stance phase (p<0.05). Third, there were significant differences in kinematic parameters in the study group during the swing phase (p<0.05). Conclusion: The gait pattern of patients with chronic low back pain is characterized by more rigid patterns. Compared to the control group, there was a decrease in the spatio-temporal parameters and kinematic parameters in patients with chronic low back pain. These findings are expected to play a role as basic data and to form a rehabilitation program for low back pain patients.

  • PDF

Comparison of Spatio-temporal Gait Parameters between Paretic and Non-paretic Limb while Stepping over the Different Obstacle's Heights in Subjects with Stroke (편마비 환자의 장애물 높이에 따른 마비측과 비마비측 하지의 시공간적 보행변수 비교)

  • Han, Jin-Tae
    • Journal of the Korean Society of Physical Medicine
    • /
    • v.9 no.1
    • /
    • pp.69-74
    • /
    • 2014
  • PURPOSE: The aim of this study is to compare the spatio-temporal gait parameters between paretic and non-paretic limb while stepping over the different obstacle's heights in subjects with stroke. METHODS: Nine subjects with stroke were participated in this study. Subjects were asked to step over obstacles with a different height. 8 camera motion analysis system(Motion Analysis Corporation, Santa Rosa, USA) was used to measure spatio-temporal parameters. The two way repeated measurement ANOVA was used to compare spati-temporal gait parameters between paretic and non-paretic limbs while stepping over a different obstacle's height(0cm, 10cm, 20cm). RESULTS: Step width, velocity, single supoort time, and double support time were not different among obstacle's height(p>0.05) but stride length, step length, and cadence were significantly different(p>0.05). In stride length, cadence, and double support time, the interactions between obstacle's heights and limbs were not different(p>0.05) but it was significantly different in velocity, step length, and single support time(p<0.05). Velocity, stride length, cadence, and double support times were not different between paretic limb and non-paretic limb(p>0.05) but step length and single support times were significantly different between paretic limb and non-paretic limb(p<0.05). CONCLUSION: These results show that there are differences with spatio-temporal gait parameters among obstacle's heights and between paretic and non-paretic limb during obstacle crossing in subjects with stroke.

Reliability and Validity of a Smartphone-based Assessment of Gait Parameters in Patients with Chronic Stroke (만성 뇌졸중 환자에서 스마트폰을 이용한 보행변수 평가의 신뢰도와 타당도)

  • Park, Jin;Kim, Tae-Ho
    • Journal of the Korean Society of Physical Medicine
    • /
    • v.13 no.3
    • /
    • pp.19-25
    • /
    • 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.

A Missing Value Replacement Method for Agricultural Meteorological Data Using Bayesian Spatio-Temporal Model (농업기상 결측치 보정을 위한 통계적 시공간모형)

  • Park, Dain;Yoon, Sanghoo
    • Journal of Environmental Science International
    • /
    • v.27 no.7
    • /
    • pp.499-507
    • /
    • 2018
  • Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.

Characteristics of Spatio-Temporal Parameters in Parkinson's Disese During Walking (보행 시 파킨슨병 환자의 시·공간적 지표의 특성)

  • Lee, Sung-Yong;Woo, Young-Keun;Shin, Seung-Sub;Jung, Seok
    • Physical Therapy Korea
    • /
    • v.15 no.3
    • /
    • pp.35-43
    • /
    • 2008
  • The purpose of this study was to compare spatio-temporal parameters during walking between patients with idiopathic Parkinson's disease and a control group matched for age, height, and weight. Thirty-three subjects were included in this study. Fifteen normal subjects (age, $63.3{\pm}5.8$ yrs; height, $164.1{\pm}8.7$ cm; weight, $60.7{\pm}17.5$ kg) and eighteen patients (age, $64.0{\pm}7.7$ yrs; height, $164.7{\pm}7.3$ cm; weight, $63.6{\pm}7.7$ kg) participated in the study. The Vicon 512 Motion analysis system was used for gait analysis in each group during walking, with and without an obstacle. The measured spatio-temporal parameters were cadence, walking speed, stride time, step time, single limb support time, double limb support time, stride length, and step length. Results in stride length and step length, when walking without an obstacle, showed a significantly greater decrease in the patient group compared to the control group. During walking with an obstacle, the patient group showed a significantly greater decrease in the step length as compared to the control group. For the control group, there were significant decreases in parameters of cadence and walking speed and increases in parameters of stride time, step time, and single limb support time when walking with an obstacle. The patient group had lower cadence and walking speed and higher stride time, step time, and single limb support time during walking with an obstacle than in walking without an obstacle. These results suggest that patients with Parkinson's disease who walk over an obstacle can decrease cadence, stride length, and step length. Further study is needed, performed with more obstacles and combined with other external cues, such as visual or acoustic guides.

  • PDF

Robust Traffic Monitoring System by Spatio-Temporal Image Analysis (시공간 영상 분석에 의한 강건한 교통 모니터링 시스템)

  • 이대호;박영태
    • Journal of KIISE:Software and Applications
    • /
    • v.31 no.11
    • /
    • pp.1534-1542
    • /
    • 2004
  • A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.

Extended Adaptive Spatio-Temporal Auto-Regressive Model for Video Sequence (동영상에서의 확장된 시공간 적응적 Auto-regressive 모델의 연구)

  • Doo, Seok-Joo;Kang, Moon-Gi
    • Journal of the Korean Institute of Telematics and Electronics S
    • /
    • v.36S no.11
    • /
    • pp.54-59
    • /
    • 1999
  • In this paper, a generalized auto-regressive(AR) model is proposed for linear prediction based on adaptive spatio-temporal support region(ASTSR). The conventional AR model suffers from the drawback that the prediction error increases in the edge region because the rectangular support region of the edge does not satisfy the stationary assumption. Thus, the proposed approach puts an emphasis on the formulation of a spatio-temporally adaptive support region for the AR model, called ASTSR. The ASTSR consists of two parts: the adaptive spatial support region(ASSR) connected with edges and the adaptive temporal support region(ATSR) related to temporal discontinuities. The AR model based on ASTSR not only produces more accurate model parameters but also reduces the computational complexity in the motion picture restoration.

  • PDF

Soil Moisture Estimation and Drought Assessment at the Spatio-Temporal Scales using Remotely Sensed Data: (I) Soil Moisture (원격탐사자료를 이용한 시⋅공간적으로 분포되어 있는 토양수분산정 및 가뭄평가:(I) 토양수분)

  • Shin, Yongchul;Choi, Kyung-Sook;Jung, Younghun;Yang, Jae E.;Lim, Kyoung-Jae
    • Journal of Korean Society on Water Environment
    • /
    • v.32 no.1
    • /
    • pp.60-69
    • /
    • 2016
  • In this study, we estimated root zone soil moisture dynamics using remotely sensed (RS) data. A soil moisture data assimilation scheme was used to derive the soil and root parameters from MODerate resolution Imaging Spectroradiometer (MODIS) data. Based on the estimated soil/root parameters and weather forcings, soil moisture dynamics were simulated at spatio-temporal scales based on a hydrological model. For calibration/validation, the Little Washita (LW13) in Oklahoma and Chungmi-cheon/Seolma-cheon sites were selected. The derived water retention curves matched the observations at LW 13. Also, the simulated soil moisture dynamics at these sites was in agreement with the Time Domain Reflectrometry (TDR)-based measurements. To test the applicability of this approach at ungauged regions, the soil/root parameters at the pixel where the Seolma-cheon site is located were derived from the calibrated MODIS-based (Chungmi-cheon) soil moisture data. Then, the simulated soil moisture was validated using the measurements at the Seolma-cheon site. The results were slightly overestimated compared to the measurements, but these findings support the applicability of this proposed approach in ungauged regions with predictable uncertainties. These findings showed the potential of this approach in Korea. Thus, this proposed approach can be used to assess root zone soil moisture dynamics at spatio-temporal scales across Korea, which comprises mountainous regions with dense forest.

Spatio-temporal estimation of air quality parameters using linear genetic programming

  • Tikhe, Shruti S.;Khare, K.C.;Londhe, S.N.
    • Advances in environmental research
    • /
    • v.6 no.2
    • /
    • pp.83-94
    • /
    • 2017
  • Air quality planning and management requires accurate and consistent records of the air quality parameters. Limited number of monitoring stations and inconsistent measurements of the air quality parameters is a very serious problem in many parts of India. It becomes difficult for the authorities to plan proactive measures with such a limited data. Estimation models can be developed using soft computing techniques considering the physics behind pollution dispersion as they can work very well with limited data. They are more realistic and can present the complete picture about the air quality. In the present case study spatio-temporal models using Linear Genetic Programming (LGP) have been developed for estimation of air quality parameters. The air quality data from four monitoring stations of an Indian city has been used and LGP models have been developed to estimate pollutant concentration of the fifth station. Three types of models are developed. In the first type, models are developed considering only the pollutant concentrations at the neighboring stations without considering the effect of distance between the stations as well the significance of the prevailing wind direction. Second type of models are distance based models based on the hypothesis that there will be atmospheric interactions between the two stations under consideration and the effect increases with decrease in the distance between the two. In third type the effect of the prevailing wind direction is also considered in choosing the input stations in wind and distance based models. Models are evaluated using Band Error and it was observed that majority of the errors are in +/-1 band.