Based on the regularity nature of lower-limb motion,an intent pattern recognition approach for above-knee prosthesis is proposed in this paper. To remedy the defects of recognizer based on electromyogram(EMG), we deve...Based on the regularity nature of lower-limb motion,an intent pattern recognition approach for above-knee prosthesis is proposed in this paper. To remedy the defects of recognizer based on electromyogram(EMG), we develop a pure mechanical sensor architecture for intent pattern recognition of lower-limb motion. The sensor system is composed of an accelerometer, a gyroscope mounted on the prosthetic socket, and two pressure sensors mounted under the sole. To compensate the delay in the control of prosthesis, the signals in the stance phase are used to predict the terrain and speed in the swing phase. Specifically, the intent pattern recognizer utilizes intraclass correlation coefficient(ICC) according to the Cartesian product of walking speed and terrain. Moreover, the sensor data are fused via DempsterShafer's theory. And hidden Markov model(HMM) is used to recognize the realtime motion state with the reference of the prior step. The proposed method can infer the prosthesis user's intent of walking on different terrain, which includes level ground,stair ascent, stair descent, up and down ramp. The experiments demonstrate that the intent pattern recognizer is capable of identifying five typical terrain-modes with the rate of 95.8%. The outcome of this investigation is expected to substantially improve the control performance of powered above-knee prosthesis.展开更多
<span style="font-family:Verdana;">Most GIS databases contain data errors. The quality of the data sources such as traditional paper maps or more recent remote sensing data determines spatial data qual...<span style="font-family:Verdana;">Most GIS databases contain data errors. The quality of the data sources such as traditional paper maps or more recent remote sensing data determines spatial data quality. In the past several decades, different statistical measures have been developed to evaluate data quality for different types of data, such as nominal categorical data, ordinal categorical data and numerical data. Although these methods were originally proposed for medical research or psychological research, they have been widely used to evaluate spatial data quality. In this paper, we first review statistical methods for evaluating data quality, discuss under what conditions we should use them and how to interpret the results, followed by a brief discussion of statistical software and packages that can be used to compute these data quality measures.</span>展开更多
Background:The size of the glenoid bone defect is an important index in selecting the appropriate treatment for anterior shoulder instability.However,the reliability of glenoid bone defect measurement is controversial...Background:The size of the glenoid bone defect is an important index in selecting the appropriate treatment for anterior shoulder instability.However,the reliability of glenoid bone defect measurement is controversial.The purpose of the present study was to investigate the reliabilities of measurements of the glenoid bone defect on computed tomography and to explore the predisposing factors leading to inconsistency of these measurements.Methods:The study population comprised 69 consecutive patients who underwent surgery for recurrent anterior shoulder dislocation in Peking University Fourth School of Clinical Medicine from March 2016 to January 2017.The glenoid bone defect was measured by three surgeons on‘self-confirmed’and‘designated’3-D en-face views,and repeated after an interval of 3 months.Measurements included the ratio of the defect area to the best-fit circle area,and the ratio of the defect width to the diameter of the best-fit circle.The inter-and intra-observer reliabilities of the measurements were evaluated using intraclass correlation coefficients(ICCs).The maximum absolute inter-and intra-observer differences and the cumulative percentages of cases with inter-and intraobserver differences greater than these respective levels were calculated.Results:Almost all linear defect values were bigger than the areal defect values.The inter-observer ICCs for the areal defect were 0.557 and 0.513 in the‘self-confirmed’group and 0.549 and 0.431 in the‘designated’group.The inter-observer reliabilities for the linear defect were moderate or fair in the‘self-confirmed’group(ICC=0.446,0.374)and‘designated’group(ICC=0.402,0.327).The ICCs for intra-observer measurements were higher than those for inter-observer measurements.The respective maximum interand intra-observer absolute differences were 13.9%and 13.2%in the‘self-confirmed’group,and 15.8%and 9.8%in the‘designated’group.Conclusions:The areal measurement of the glenoid bone defect is more reliable than the linear measurement.The reliability of the glenoid defect areal measurement is moderate or worse,suggesting that a more accurate and objective measurement method is needed in both en-face view and best-fit circle determination.Subjective factors affecting the glenoid bone loss measurement should be minimized.展开更多
基金supported in part by the National Nature Science Fundation(61174009,61203323)Youth Foundation of Hebei Province(F2016202327)+3 种基金the Colleges and Universities in Hebei Province Science and Technology Research Project(ZC2016020)supported in part by Key Project of NSFC(61533009)111 Project(B08015)Research Project(JCYJ20150403161923519)
文摘Based on the regularity nature of lower-limb motion,an intent pattern recognition approach for above-knee prosthesis is proposed in this paper. To remedy the defects of recognizer based on electromyogram(EMG), we develop a pure mechanical sensor architecture for intent pattern recognition of lower-limb motion. The sensor system is composed of an accelerometer, a gyroscope mounted on the prosthetic socket, and two pressure sensors mounted under the sole. To compensate the delay in the control of prosthesis, the signals in the stance phase are used to predict the terrain and speed in the swing phase. Specifically, the intent pattern recognizer utilizes intraclass correlation coefficient(ICC) according to the Cartesian product of walking speed and terrain. Moreover, the sensor data are fused via DempsterShafer's theory. And hidden Markov model(HMM) is used to recognize the realtime motion state with the reference of the prior step. The proposed method can infer the prosthesis user's intent of walking on different terrain, which includes level ground,stair ascent, stair descent, up and down ramp. The experiments demonstrate that the intent pattern recognizer is capable of identifying five typical terrain-modes with the rate of 95.8%. The outcome of this investigation is expected to substantially improve the control performance of powered above-knee prosthesis.
文摘<span style="font-family:Verdana;">Most GIS databases contain data errors. The quality of the data sources such as traditional paper maps or more recent remote sensing data determines spatial data quality. In the past several decades, different statistical measures have been developed to evaluate data quality for different types of data, such as nominal categorical data, ordinal categorical data and numerical data. Although these methods were originally proposed for medical research or psychological research, they have been widely used to evaluate spatial data quality. In this paper, we first review statistical methods for evaluating data quality, discuss under what conditions we should use them and how to interpret the results, followed by a brief discussion of statistical software and packages that can be used to compute these data quality measures.</span>
文摘Background:The size of the glenoid bone defect is an important index in selecting the appropriate treatment for anterior shoulder instability.However,the reliability of glenoid bone defect measurement is controversial.The purpose of the present study was to investigate the reliabilities of measurements of the glenoid bone defect on computed tomography and to explore the predisposing factors leading to inconsistency of these measurements.Methods:The study population comprised 69 consecutive patients who underwent surgery for recurrent anterior shoulder dislocation in Peking University Fourth School of Clinical Medicine from March 2016 to January 2017.The glenoid bone defect was measured by three surgeons on‘self-confirmed’and‘designated’3-D en-face views,and repeated after an interval of 3 months.Measurements included the ratio of the defect area to the best-fit circle area,and the ratio of the defect width to the diameter of the best-fit circle.The inter-and intra-observer reliabilities of the measurements were evaluated using intraclass correlation coefficients(ICCs).The maximum absolute inter-and intra-observer differences and the cumulative percentages of cases with inter-and intraobserver differences greater than these respective levels were calculated.Results:Almost all linear defect values were bigger than the areal defect values.The inter-observer ICCs for the areal defect were 0.557 and 0.513 in the‘self-confirmed’group and 0.549 and 0.431 in the‘designated’group.The inter-observer reliabilities for the linear defect were moderate or fair in the‘self-confirmed’group(ICC=0.446,0.374)and‘designated’group(ICC=0.402,0.327).The ICCs for intra-observer measurements were higher than those for inter-observer measurements.The respective maximum interand intra-observer absolute differences were 13.9%and 13.2%in the‘self-confirmed’group,and 15.8%and 9.8%in the‘designated’group.Conclusions:The areal measurement of the glenoid bone defect is more reliable than the linear measurement.The reliability of the glenoid defect areal measurement is moderate or worse,suggesting that a more accurate and objective measurement method is needed in both en-face view and best-fit circle determination.Subjective factors affecting the glenoid bone loss measurement should be minimized.
