摘要:
A method for providing personalized recommendations to an individual, relating to monitoring his or her weight, comprising the steps of /a/ obtaining a plurality of prior weighings for the individual concerned, each weighing giving the total weight and the body fat percentage, /b/ deriving a characteristic curve (S1) for the individual by associating at least the total weight and the fat body mass, /c/ obtaining a target total weight (P2) for the user to achieve by the end of a target period, and therefore a target total weight change, /d/ deducing a target number of calories to burn, corresponding to target changes in the fat body mass and lean body mass deduced from the total weight change, /e/ providing the user with personalized instructions on exercise and/or diet.
摘要翻译:一种用于向个人提供与监测他或她的体重有关的个性化建议的方法,其包括以下步骤:为所述个体获得多个先前的称重,每个称重给出总体重和身体脂肪百分比,/ b 通过至少将总体重和脂肪体重相关联来得出个体的特征曲线(S1),/ c /获得用户在目标周期结束后实现的目标总重量(P2),因此 目标总重量变化,/ d /推导目标燃烧卡路里数,对应于从总重量变化推断的脂肪体重和瘦体重的目标变化,/ e /向用户提供运动的个性化指示, /或饮食。
摘要:
A method to monitor a data of interest of an individual (U) and give advice to said individual, said method comprising: a—collect said data of interest and a plurality of life parameters, b—monitor the evolution over time of said data of interest, c—detect an unexpected/inadvertent deviation in the evolution of data of interest, forming a break event, occurred at a first instant (T1), d—store the previously collected values of the plurality of life parameters over a first time window preceding said break event, to form a reference values collection of life parameters, attached to said individual and to the break event, and later: e—collect over time, the values of the plurality of life parameters, f—compare said lately collected values of life parameters to the reference values collection of life parameters stored, and if they are similar, give a notice to the user, whereby the user can be warned of a possible imminent deviation related to the data of interest.
摘要:
A method to monitor a data of interest of an individual (U) and give advice to said individual, said method comprising: a—collect said data of interest and a plurality of life parameters, b—monitor the evolution over time of said data of interest, c—detect an unexpected/inadvertent deviation in the evolution of data of interest, forming a break event, occurred at a first instant (T1), d—store the previously collected values of the plurality of life parameters over a first time window preceding said break event, to form a reference values collection of life parameters, attached to said individual and to the break event, and later: e—collect over time, the values of the plurality of life parameters, f—compare said lately collected values of life parameters to the reference values collection of life parameters stored, and if they are similar, give a notice to the user, whereby the user can be warned of a possible imminent deviation related to the data of interest.
摘要:
A method for determining the weight of an entity/item to be weighed on a weighing device (1), the weighing device comprising at least a weight sensor and a control unit (4),the method comprising the following steps: /a/ collecting weight raw samples (WSi) of the total weight sensed at the weight sensor(s), at a sampling frequency (F0), and converting each of the weight raw samples (WSi) into digitalized weight raw samples (DSi), /b/ entering sequentially each of the digitalized weight raw samples (DSi) into a Butterworth filter, the latter issuing filtered weight samples (FSi), /c/ defining a rolling window (RW) containing a parametrized number NS of latest filtered weight samples (FSi), /d1/ determining, in the rolling window, the minimum (MIN) and maximum (MAX) values of filtered weight samples, /d2/ comparing the value of MAX−MIN with regard to a parametrized Threshold (T), /e/ if MAX−MIN is greater than Threshold (T), repeat steps /a/ to /d2/, and as soon as MAX−MIN is less than Threshold (T), output a final weight value (DV), obtained from one or more of the most recent filtered weight samples.
摘要:
A method for determining the weight of an entity/item to be weighed on a weighing device (1), the weighing device comprising at least a weight sensor and a control unit (4),the method comprising the following steps: /a/ collecting weight raw samples (WSi) of the total weight sensed at the weight sensor(s), at a sampling frequency (F0), and converting each of the weight raw samples (WSi) into digitalized weight raw samples (DSi), /b/ entering sequentially each of the digitalized weight raw samples (DSi) into a Butterworth filter, the latter issuing filtered weight samples (FSi), /c/ defining a rolling window (RW) containing a parametrized number NS of latest filtered weight samples (FSi), /d1/ determining, in the rolling window, the minimum (MIN) and maximum (MAX) values of filtered weight samples, /d2/ comparing the value of MAX−MIN with regard to a parametrized Threshold (T), /e/ if MAX−MIN is greater than Threshold (T), repeat steps/a/ to /d2/, and as soon as MAX−MIN is less than Threshold (T), output a final weight value (DV), obtained from one or more of the most recent filtered weight samples.
摘要:
A method implemented in a system which comprises a lightweight personal wearable monitoring device, supplied by a battery, comprising an accelerometer, a processing unit, a display, a remote server, said method comprising the steps: /a/ collecting, from a plurality of individuals caused to practice various physical activities from a set of predefined activities, acceleration data from sensing devices placed on each of said individuals, /b/ defining N small data-size specific metrics, computed from acceleration signals, which allow to define a global activity classifier, /c/ acquiring, at a first monitoring device worn by a first user, acceleration signals from the accelerometer of the first monitoring device, /d/ calculating, at the first monitoring device, over each lapsed time unit T1, specific metrics values from the sensed signals, to form a series of specific metrics values, /e/ send them to the processing unit, /f/ allocate an activity type for each time unit together with corresponding specific metrics values of the received series, to form a time chart of activity types presumably performed by the first user over a second period T2, /g/ display the time chart of activity types presumably performed by the first user on the display and allow the first user to confirm or correct partly the type of activity performed over the second period, and allow correction by the first user.
摘要:
A method for providing personalized recommendations to an individual, relating to monitoring his or her weight, comprising the steps of /a/ obtaining a plurality of prior weighings for the individual concerned, each weighing giving the total weight and the body fat percentage, /b/ deriving a characteristic curve (S1) for the individual by associating at least the total weight and the fat body mass, /c/ obtaining a target total weight (P2) for the user to achieve by the end of a target period, and therefore a target total weight change, /d/ deducing a target number of calories to burn, corresponding to target changes in the fat body mass and lean body mass deduced from the total weight change, /e/ providing the user with personalized instructions on exercise and/or diet.
摘要:
The method for optimizing light and sound programs for a falling asleep phase and for an awakening phase of a first user, in a system comprising, for the first user and other users, a bedside device, a bio parameter sensor, a smartphone, and additionally for all users a central server, with: /a1/ collecting, with regard to the first user, sleep data and sleep context data, said sleep data comprising at least light and sound program played for the falling asleep phase and for the awakening phase, bio parameters and sleep patterns sequence deduced therefrom, said sleep context data comprising at least previous daytime activity such as, sending this data to the central server, /a2/ repeat /a1/ for other users, /b1/ building a user-specific model of each user sleep behavior, /c/ comparing user-specific models to define groups of similar users, each group of users being allocated with a group meta-model with decision rules and preferred playlist of sound tracks, /d/ sending the group meta-model from the server to the bedside device or to the smartphone of the first user, /e/ displaying to the first user, using the group meta-model and in function of the time to go to sleep, a recommended list of light and sound programs or a particular light and sound program, namely a single choice, for the upcoming falling asleep phase and/or the next upcoming wakeup phase.
摘要翻译:一种用于在第一用户和其他用户中为睡眠阶段和第一用户的唤醒阶段优化光和声程序的方法,所述系统包括用于第一用户和其他用户的床头设备,生物参数传感器,智能电话机以及附加 对于所有用户,具有:/ a1 / collect的中央服务器,对于第一用户,睡眠数据和睡眠上下文数据,所述睡眠数据至少包括为睡眠阶段和唤醒阶段播放的光和声节目, 生物参数和睡眠模式序列,所述睡眠上下文数据至少包括先前的白天活动,例如将该数据发送到中央服务器,/ a2 / repeat / a1 /用于其他用户,/ b1 /构建用户特定模型 每个用户的睡眠行为,/ c /比较用户特定模型以定义类似用户的组,每组用户被分配具有决策规则的组元模型和声轨的首选播放列表,/ d /发送组元 -m odel从服务器到床边设备或第一用户的智能手机,/ e /显示给第一个用户,使用组元模型,并且具有时间去睡觉的功能,推荐的光和声音列表 节目或特定的光和声节目,即单一选择,用于即将到来的睡眠阶段和/或下一个即将到来的唤醒阶段。
摘要:
A method implemented in a system which comprises a lightweight personal wearable monitoring device, supplied by a battery, comprising an accelerometer, a processing unit, a display, a remote server, said method comprising the steps: /a/ collecting, from a plurality of individuals caused to practice various physical activities from a set of predefined activities, acceleration data from sensing devices placed on each of said individuals, /b/ defining N small data-size specific metrics, computed from acceleration signals, which allow to define a global activity classifier, /c/ acquiring, at a first monitoring device worn by a first user, acceleration signals from the accelerometer of the first monitoring device, /d/ calculating, at the first monitoring device, over each lapsed time unit T1, specific metrics values from the sensed signals, to form a series of specific metrics values, /e/ send them to the processing unit, /f/ allocate an activity type for each time unit together with corresponding specific metrics values of the received series, to form a time chart of activity types presumably performed by the first user over a second period T2, /g/ display the time chart of activity types presumably performed by the first user on the display and allow the first user to confirm or correct partly the type of activity performed over the second period, and allow correction by the first user.
摘要:
A method implemented in a system which comprises a lightweight personal wearable monitoring device, supplied by a battery, comprising an accelerometer, a processing unit, a display, a remote server, said method comprising the steps: /a/ collecting, from a plurality of individuals caused to practice various physical activities from a set of predefined activities, acceleration data from sensing devices placed on each of said individuals, /b/ defining N small data-size specific metrics, computed from acceleration signals, which allow to define a global activity classifier, /c/ acquiring, at a first monitoring device worn by a first user, acceleration signals from the accelerometer of the first monitoring device, /d/ calculating, at the first monitoring device, over each lapsed time unit T1, specific metrics values from the sensed signals, to form a series of specific metrics values, /e/ send them to the processing unit, /f/ allocate an activity type for each time unit together with corresponding specific metrics values of the received series, to form a time chart of activity types presumably performed by the first user over a second period T2, /g/ display the time chart of activity types presumably performed by the first user on the display and allow the first user to confirm or correct partly the type of activity performed over the second period, and allow correction by the first user.