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公开(公告)号:KR1020130029223A
公开(公告)日:2013-03-22
申请号:KR1020110092491
申请日:2011-09-14
Applicant: 한국전자통신연구원
Abstract: PURPOSE: A gait training system, data processing unit thereof, and an operating method of the data processing unit are provided to prevent generation of disease relating to a musculoskeletal system. CONSTITUTION: A wireless communication unit(210) receives acceleration data from a gait sensor device(100). The wireless communication unit receives acceleration data of the moving direction of a pedestrian, acceleration data of the left and right direction of a pedestrian and acceleration data of the upward and downward direction of a pedestrian from the gait sensor device. A 11-shaped gait detection unit(230) judges whether a pedestrian walk in a 11 shape or not using the acceleration data. A display unit(240) provides the information of whether the 11-shaped gait is kept or not. [Reference numerals] (100) Gait sensor device; (110) Acceleration sensor device; (120,210) Wireless communication unit; (200) Data processing device; (220) Preprocessing unit; (230) 11-shaped gait detection unit; (240) Display unit; (250) Data storage unit; (260) Control unit
Abstract translation: 目的:提供一种步态训练系统,其数据处理单元和数据处理单元的操作方法,以防止与肌肉骨骼系统相关的疾病的产生。 构成:无线通信单元(210)从步态传感器装置(100)接收加速度数据。 无线通信单元从步态传感器装置接收行人的移动方向的加速度数据,行人的左右方向的加速度数据和行人的上下方向的加速度数据。 11形态的步态检测单元(230)使用加速度数据判断行人是否为11个形状。 显示单元(240)提供是否保持11形步态的信息。 (附图标记)(100)步态传感器装置; (110)加速度传感器装置; (120,210)无线通信单元; (200)数据处理装置; (220)预处理单元; (230)11形步态检测单元; (240)显示单元; (250)数据存储单元; (260)控制单元
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公开(公告)号:KR1020110072328A
公开(公告)日:2011-06-29
申请号:KR1020090129206
申请日:2009-12-22
Applicant: 한국전자통신연구원
IPC: A61B5/103
CPC classification number: A61B5/1038 , A61B5/6807 , A61B2562/0247 , A61B2562/046
Abstract: PURPOSE: A method for analyzing a walking pattern is provided to calculate correctly a moving track of a COP(Center Of Pressure) by reflecting a characteristic of an FSR(Force Sensing Resistor) sensor and a characteristic of a frame structure of a foot. CONSTITUTION: A plurality of FSR sensors measures a foot pressure value(S310). The output values of the FSR sensors are pre-processed(S320). A maximum pressure local region is searched(S330). A COP calculation process for the maximum pressure local region is performed(S340). The calculated COP is added to a COP moving track (S350).
Abstract translation: 目的:提供一种分析步行模式的方法,通过反映FSR(力感测电阻)传感器的特性和脚架结构的特性,正确计算COP(压力中心)的移动轨迹。 构成:多个FSR传感器测量脚压值(S310)。 FSR传感器的输出值被预处理(S320)。 搜索最大压力局部区域(S330)。 执行最大压力局部区域的COP计算处理(S340)。 计算出的COP被添加到COP移动轨迹(S350)。
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公开(公告)号:KR1020110071727A
公开(公告)日:2011-06-29
申请号:KR1020090128368
申请日:2009-12-21
Applicant: 한국전자통신연구원
CPC classification number: G01S19/14 , A43B3/0005 , A61B5/002 , A61B5/1112 , A61B5/1123 , A61B5/6807 , A61B2562/0219 , A61B2562/0247 , A61B2562/046
Abstract: PURPOSE: Smart footwear is provided to remove an inconvenience of elderly people wearing new apparatus and to measure an active mass and a sense of isolation in a daily life. CONSTITUTION: The smart footwear includes a film type leading sensor(110), which measures a change of power added to a smart footwear user as a resistance value, an acceleration sensor(120) measuring an acceleration value according to movement changes of the user, and a microcontroller(130), which predicts a current state and activity mass of the user by using the resistance value and the acceleration value, and creates status information and active mass information of user.
Abstract translation: 目的:提供智能鞋类,消除身患新装置的老年人的不便,并在日常生活中测量活跃的身体和隔离感。 构成:智能鞋类包括胶片型领先传感器(110),其测量作为电阻值添加到智能鞋类用户的功率变化;加速度传感器(120),其根据用户的移动改变来测量加速度值; 以及微控制器(130),其通过使用电阻值和加速度值来预测用户的当前状态和活动质量,并且创建用户的状态信息和活动质量信息。
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公开(公告)号:KR1020110034969A
公开(公告)日:2011-04-06
申请号:KR1020090092483
申请日:2009-09-29
Applicant: 한국전자통신연구원
CPC classification number: G01C22/006 , A43B3/0005 , A61B5/1116 , A61B5/6807 , G06F19/00 , G06F19/3418 , G06F19/3481
Abstract: PURPOSE: A motion recognizing system using footwear for recognizing a motion is provided to correct the posture of a wearer by using information about the motion of a foot, a three dimensional position and the balance of the body of the wearer. CONSTITUTION: Motion recognition footwear(10) measures a height, an acceleration, and the pressure of a foot, preprocesses the measured signal, and transmits the signal to the outside. An information processing terminal(20) analyzes the signal received from the motion recognition footwear, obtains the three dimensional position, the motion of the foot, and the balance of the body of wearer, and provides an application service based on the obtained information.
Abstract translation: 目的:提供使用用于识别运动的鞋类的运动识别系统,以通过使用关于脚的运动,三维位置和穿戴者身体的平衡的信息来校正穿着者的姿势。 规定:运动识别鞋(10)测量脚的高度,加速度和压力,预处理测量信号,并将信号传输到外部。 信息处理终端(20)分析从运动识别鞋类接收的信号,获得三维位置,脚的运动和穿戴者身体的平衡,并根据获得的信息提供应用服务。
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公开(公告)号:KR100829867B1
公开(公告)日:2008-05-16
申请号:KR1020070038835
申请日:2007-04-20
Applicant: 한국전자통신연구원
IPC: G01N33/48
Abstract: A method for clustering gene using gene expression profile is provided to obtain an accurate clustering result with low calculation complexity without directly designating complicated and detrimental input variations determining quality of a clustering result by clustering a time series gene expression profile data set into a gene group having the similar function. A method for clustering gene using gene expression profile comprises the steps of: (a) calculating a parameter value of each orders of a linear regression model when the gene expression profile is inputted; (b) calculating an F-distribution based probability regarding each of the parameter value calculated linear regression model; and (c) after selecting the linear regression model having a minimum value of the calculated F-distribution based probability, clustering the gene in accordance with the order of the selected linear regression model, wherein the gene is clustered by an increase function or a decrease function according to a sign of the corresponding parameter value when the order of the finally selected linear regression model is 1st(linear) or at least 3rd. or is clustered by a concave function or a convex function according to the sign of the corresponding parameter value when the order of the finally selected linear regression model is 2nd(parabola).
Abstract translation: 提供了使用基因表达谱聚类基因的方法,以获得具有低计算复杂度的精确聚类结果,而没有直接指定通过将时间序列基因表达谱数据集聚集到具有以下基因组的基因组中来确定聚类结果的质量的复杂且有害的输入变异: 类似的功能。 使用基因表达谱聚类基因的方法包括以下步骤:(a)当输入基因表达谱时,计算线性回归模型的每个阶数的参数值; (b)根据参数值计算的线性回归模型计算基于F分布的概率; 和(c)在选择具有所计算的基于F分布的概率的最小值的线性回归模型之后,根据所选择的线性回归模型的顺序聚类基因,其中基因通过增加函数或减少而聚集 当最终选择的线性回归模型的顺序为1(线性)或至少3时,根据相应参数值的符号来函数。 或者当最终选择的线性回归模型的顺序为2(抛物线)时,根据相应参数值的符号,通过凹函数或凸函数进行聚类。
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公开(公告)号:KR1020170140757A
公开(公告)日:2017-12-21
申请号:KR1020160142185
申请日:2016-10-28
Applicant: 한국전자통신연구원
CPC classification number: G16H50/20 , G06N3/08 , G06N5/04 , G06N99/005
Abstract: 본발명은임상의사결정지원앙상블시스템및 그방법에관한것으로, 복수의외부의료기관으로부터수신되는기계학습을통한환자의임상예측결과를통합하여, 앙상블예측을수행함으로써, 상기환자의현재상태뿐만아니라향후상기환자의질환에대한진행상태를예측하여, 의료인의의료행위에관한신속하고정확한임상의사결정을지원하기위한시스템및 그방법에관한것이다.
Abstract translation: 本发明涉及一种临床决策支持集成系统及其方法,通过从多个外部医疗机构接收的通过机器学习整合患者的临床预测结果并执行集合预测, 本发明涉及用于预测患者疾病进展并支持关于医学人员的医疗护理行为的快速且准确的临床决策的系统和方法。
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公开(公告)号:KR1020170061223A
公开(公告)日:2017-06-05
申请号:KR1020150165491
申请日:2015-11-25
Applicant: 한국전자통신연구원
CPC classification number: G16H10/60 , G06F17/30598 , G06F17/30867 , G06F19/00 , G06N99/005 , G16H50/50 , G16H50/70
Abstract: 본발명은다차원건강데이터에대한유사사례검색방법및 그장치에관한것으로, 더욱상세하게는검색에대한계산복잡도가상당히높은시계열다변량(다차원)의특성을가지는건강데이터를검색하기위해건강데이터의포맷을변환하고학습모델을적용한특징추출을통해서건강데이터의차원을줄임으로써, 검색을위한계산복잡도를줄이고, 효율적인유사사례검색이가능한검색방법및 그장치를제공하고자하는것이다.
Abstract translation: 本发明类似的情况下的检索方法,以及涉及一种装置,更具体地,涉及健康数据以检索与计算复杂度的特性的健康数据的格式是用于搜索多维健康数据显著更高的时间序列的多变量的(多维) 通过应用学习模型通过特征提取减少健康数据的维度,从而降低搜索和有效搜索类似病例的计算复杂度。
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公开(公告)号:KR1020170060557A
公开(公告)日:2017-06-01
申请号:KR1020160043652
申请日:2016-04-08
Applicant: 한국전자통신연구원
CPC classification number: G06Q50/22 , A61B5/021 , A61B5/107 , A61B5/14532 , G16H10/60
Abstract: 본발명에따른건강관리장치의미래건강예측방법은, 사용자의건강정보를입력받는단계, 상기건강정보를전처리하는단계, 상기전처리된건강정보를이용하여건강데이터베이스로부터유사사례들을검색하는단계, 상기유사사례들을근거로하여상기사용자의건강패턴분석및 미래의건강계측치를예측하는단계, 상기분석된건강패턴혹은상기예측된건강계측치에대응하는건강힐링플랜을설계하는단계, 및상기건강힐링플랜에대응하는건강힐링정보를디스플레이장치로출력하는단계를포함할수 있다.
Abstract translation: 根据本发明的预测健康护理装置的未来健康的方法包括以下步骤:输入用户的健康信息,预处理健康信息,使用预处理的健康信息从健康数据库搜索类似病例, 基于类似病例分析用户的健康模式并预测未来的健康测量,设计与分析的健康模式或预测的健康测量相对应的健康康复计划, 并将相应的健康康复信息输出到显示设备。
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