A wearable sensor device can include at least one LED and a light sensor for generating a photoplethysmogram ("PPG") from light emitted by the at least one LED. The wearable sensor device can also include a processing unit that is configured to process the PPG to produce a highly reliable representation of the wearer's pulse.
A61B 5/1455 - Mesure des caractéristiques du sang in vivo, p. ex. de la concentration des gaz dans le sang ou de la valeur du pH du sang en utilisant des capteurs optiques, p. ex. des oxymètres à photométrie spectrale
A61B 5/00 - Mesure servant à établir un diagnostic Identification des individus
Aspects of the present invention relate to analysis of physiological data sequences and activity data recorded while a user participates in various activities. Some aspects relate to alert or messaging system and methods whereby messages are automatically generated when a condition in the physiological or activity data is satisfied. Messages may be automatically formatted with physiological and/or activity data as well as other fields and content. Each message condition may be related to a unique recipient list and message content template.
A61B 5/02 - Détection, mesure ou enregistrement en vue de l'évaluation du système cardio-vasculaire, p. ex. mesure du pouls, du rythme cardiaque, de la pression sanguine ou du débit sanguin
H04M 1/02 - Caractéristiques de structure des appareils téléphoniques
G06Q 50/22 - Aide sociale ou assistance sociale, p. ex. activités de développement communautaire ou services de consultation
3.
SYSTEMS AND METHODS FOR WEARABLE HEALTH MONITORING
Aspects of the present invention relate to recording physiological data sequences while a user participates in various activities. These activities may comprise awake activities, periods of sleep and transitions between sleep and activity. Record sequences are recorded and maintained for a period of time including many cycles of activity. The physiological activity data sequences may then be analyzed to identify trends that lead up to specific events that have occurred. The physiological data may also be compared to known trends to alert a user to trends that may lead to adverse events. Some embodiments comprise physiological sequence records that document multiple sleep and activity cycles over an extended period of time.
Aspects of the present invention relate to analysis of physiological data sequences and activity data recorded while a user participates in various activities. Some aspects relate to alert or messaging system and methods whereby messages are automatically generated when a condition in the physiological or activity data is satisfied. Messages may be automatically formatted with physiological and/or activity data as well as other fields and content. Each message condition may be related to a unique recipient list and message content template.
An LED of a wearable sensor device can be driven less frequently while still obtaining an accurate biometric sample. By reducing how frequently the LED is driven, the power required to operate the wearable sensor device is likewise reduced. To allow the LED to be driven less frequently while still obtaining an accurate biometric sample, a known lighting profile of an LED can be employed with a matched filter to generate a biometric sample from a number of samples taken while the LED is lighting. In this way, the LED only needs to be lighted for a short period of time and a reduced amount of data is stored both of which minimize the power requirements of the wearable sensor device.
A61B 5/1455 - Mesure des caractéristiques du sang in vivo, p. ex. de la concentration des gaz dans le sang ou de la valeur du pH du sang en utilisant des capteurs optiques, p. ex. des oxymètres à photométrie spectrale
6.
DYNAMIC ADJUSTMENT OF SAMPLING RATE BASED ON A STATE OF THE USER
An activity classification server receives raw data from one or more activity -tracking devices worn by a user and processes the raw data to classify the user's activities into one or more identifiable states. The activity-tracking devices operate at a given sampling rate to collect the raw data. To optimize power usage, among other things, the activity classification server adjusts the sampling rate of the activity-tracking devices based on the state of the user at any given time. Therefore, the activity -tracking devices collect raw data at different sampling rates depending on the type of activity in which the user wearing those devices is engaged.
A61B 5/11 - Mesure du mouvement du corps entier ou de parties de celui-ci, p. ex. tremblement de la tête ou des mains ou mobilité d'un membre
G01C 22/00 - Mesure de la distance parcourue sur le sol par des véhicules, des personnes, des animaux ou autres corps solides en mouvement, p. ex. en utilisant des odomètres ou en utilisant des podomètres
7.
SYSTEMS AND METHODS FOR CONNECTED DISPENSING AND STORAGE
Aspects of the present invention relate to a container for selective dispensing of a contained substance. Some aspects relate to wireless communication connections for communicating container programming data and notifications to a user or third parties. Some aspects relate to selective operation related to the proximity of a wearable component or related to a user's physiological parameters.
A61J 7/04 - Dispositions pour l'indication ou le rappel du moment où l'on doit prendre des médicaments, p. ex. distributeurs programmés
A61J 3/00 - Dispositifs ou procédés spécialement conçus pour donner à des produits pharmaceutiques une forme physique déterminée ou une forme propre à leur administration
A61M 5/172 - Moyens pour commander l'écoulement des agents vers le corps ou pour doser les agents à introduire dans le corps, p. ex. compteurs de goutte-à-goutte électriques ou électroniques
8.
ACTIVITY CLASSIFICATION BASED ON CLASSIFICATION OF REPETITION REGIONS
A wearable device allows the tracking of human movements during activity, such as while exercising or playing a sport. To improve user experience with the wearable device, an activity classification server classifies activities and repetitions of the activity. To further improve user experience, the activity classification server can prompt the user to perform an activity and identify the activity while the user performs the prompted activity. The user can also indicate to the device an election to perform a particular activity without being prompted by the device and the user can classify the activity by indicating to the device what activity the user will perform.
Sensor data obtained from a wearable sensor device can be correlated with sensor data obtained from a smart phone or other mobile device. The correlation of the data from the two sources can enable the determination of why a person performs some action during sleep. In a particular example, motion data obtained from a wearable sensor device can be correlated with audio or visual data obtained by a sensor on a smart phone. In this way, it can be determined whether a person moved in response to a sound or light perceived during sleep. Additionally, the correlation of the data from the two sources can also provide additional information about how a user performs an activity such as exercise.
A platform is provided for generating, transmitting, and processing sensor data. The platform can provide various components with which a sensor can interface to allow the sensor to provide sensor data using a common mechanism. The platform can include an API which provides a common interface for communicating with a wearable sensor device. The API can allow an application to receive activity recognition and biometric data from one or more sensors in a processed and usable format thereby facilitating the usage of such data. The platform can also comprise a sensor data processor configured to process raw sensor data into a usable format for consumption by other applications, and a sensor data interface for transmitting the raw sensor data to a mobile device for processing by the sensor data processor.
The present invention is directed to providing customized versions of firmware to a wearable sensor device. The customized versions of the firmware can allow one or more sensors in the wearable sensor device to perform in a manner that is most optimal for a particular user or the particular manner in which the wearable sensor device is used. In some cases, the customizations can include causing the sensors to use a sampling rate that is optimal for one or more activities that the particular user intends to perform while wearing the wearable sensor device.
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