Abstract: Wearable pulse pressure wave sensing devices are presented that generally provide a non-intrusive way to measure a pulse pressure wave travelling through an artery using a wearable device. In one implementation, the device includes an array of pressure sensors disposed on a mounting structure which is attachable to a user on an area proximate to an underlying artery. Each of the pressure sensors is capable of being mechanically coupled to the skin of the user proximate to the underlying artery. In addition, there are one or more arterial location sensors disposed on the mounting structure which identify a location on the user's skin likely overlying the artery. A pulse pressure wave is then measured using the pressure sensor of the array closest to the identified location.

Abstract: Wearable pulse pressure wave sensing devices are presented that generally provide a non-intrusive way to measure a pulse pressure wave travelling through an artery using a wearable device. In one implementation, the device includes an array of pressure sensors disposed on a mounting structure which is attachable to a user on an area proximate to an underlying artery. Each of the pressure sensors is capable of being mechanically coupled to the skin of the user proximate to the underlying artery. In addition, there are one or more arterial location sensors disposed on the mounting structure which identify a location on the user's skin likely overlying the artery. A pulse pressure wave is then measured using the pressure sensor of the array closest to the identified location.

Abstract: A first data window of a pulse waveform signal comprising a first number of samples is analyzed to determine a level of confidence that a pulse sensing device is placed correctly. If an initial level of confidence is met, the user is given positive feedback, and a second data window of a pulse waveform signal comprising a second, larger number of samples is analyzed. If an increased level of confidence is met, the user is given increased positive feedback. If a level of confidence is not met, the user is given negative feedback. If a final level of confidence is met, the user is given feedback that the pulse sensing device is placed correctly.

Abstract: A wrist-worn device heart-monitoring device is presented. The wrist-worn heart-monitoring device includes a radial tonometer configured to output a pressure signal indicating a pulse pressure wave at a user's wrist, two or more electrodes configured to output an electrical signal indicating a user's heart has been commanded to contract, and a microphone configured to output an audio signal indicating a closing of a user's aortic valve. The wrist-worn heart-monitoring device further includes a pulse transit time monitor configured to calculate a pre-ejection period of the user's heart based on at least the pressure, electrical, and audio signals, and calculate a pulse transit time based on at least the pre-ejection period, the pressure signal, and the electrical signal.

Abstract: Wearable pulse pressure wave sensing devices are presented that generally provide a non-intrusive way to measure a pulse pressure wave travelling through an artery using a wearable device. In one implementation, the device includes an array of pressure sensors disposed on a mounting structure which is attachable to a user on an area proximate to an underlying artery. Each of the pressure sensors is capable of being mechanically coupled to the skin of the user proximate to the underlying artery. In addition, there are one or more arterial location sensors disposed on the mounting structure which identify a location on the user's skin likely overlying the artery. A pulse pressure wave is then measured using the pressure sensor of the array closest to the identified location.

Abstract: A wrist-worn pressure sensing device includes a pressure sensor. The wrist-worn pressure sensing device also includes a first strap that sets the position of the pressure sensor on a wearer's wrist and a second strap that engages with the first strap to adjust the overall length of the strap without moving the set position of the pressure sensor on the wearer's wrist.

Abstract: A wearable tonometer is provided, comprising a sensing device. The sensing device may include a pressure sensor configured to measure a pulse pressure wave in an artery of user. The sensing device may include a resiliently deformable pad or pad-cap structure positioned on a sensing surface side of the pressure sensor and configured to contact skin of the user proximate the artery. The wearable tonometer may include a band that holds the sensing device in contact with the skin. In some embodiments, the sensing device may include a rigid internal structure configured to transmit the pulse pressure wave. In some embodiments, the wearable tonometer may include an adjustment mechanism configured to move the sensing device relative to the band. In some embodiments, the wearable tonometer may include a second resiliently deformable pad-cap structure, and a solid plate attached to the resiliently deformable pad-cap structures and the band.

Abstract: A “Food Logger” provides various approaches for learning or training one or more image-based models (referred to herein as “meal models”) of nutritional content of meals. This training is based on one or more datasets of images of meals in combination with “meal features” that describe various parameters of the meal. Examples of meal features include, but are not limited to, food type, meal contents, portion size, nutritional content (e.g., calories, vitamins, minerals, carbohydrates, protein, salt, etc.), food source (e.g., specific restaurants or restaurant chains, grocery stores, particular pre-packaged foods, school meals, meals prepared at home, etc.). Given the trained models, the Food Logger automatically provides estimates of nutritional information based on automated recognition of new images of meals provided by (or for) the user. This nutritional information is then used to enable a wide range of user-centric interactions relating to food consumed by individual users.

Abstract: A wearable sensing band is presented that generally provides a non-intrusive way to measure a person's cardiovascular vital signs including pulse transit time and pulse wave velocity. The band includes a strap with one or more primary electrocardiography (ECG) electrodes which are in contact with a first portion of the user's body, one or more secondary ECG electrodes, and one or more pulse pressure wave arrival (PPWA) sensors. The primary and secondary ECG electrodes detect an ECG signal whenever the secondary ECG electrodes make electrical contact with the second portion of the user's body, and the PPWA sensors sense an arrival of a pulse pressure wave to the first portion of the user's body from the user's heart. The ECG signal and PPWA sensor(s) readings are used to compute at least one of a pulse transit time (PTT) or a pulse wave velocity (PWV) of the user.

Abstract: A “Food Logger” provides various approaches for learning or training one or more image-based models (referred to herein as “meal models”) of nutritional content of meals. This training is based on one or more datasets of images of meals in combination with “meal features” that describe various parameters of the meal. Examples of meal features include, but are not limited to, food type, meal contents, portion size, nutritional content (e.g., calories, vitamins, minerals, carbohydrates, protein, salt, etc.), food source (e.g., specific restaurants or restaurant chains, grocery stores, particular pre-packaged foods, school meals, meals prepared at home, etc.). Given the trained models, the Food Logger automatically provides estimates of nutritional information based on automated recognition of new images of meals provided by (or for) the user. This nutritional information is then used to enable a wide range of user-centric interactions relating to food consumed by individual users.

Abstract: A “Food Logger” provides various approaches for learning or training one or more image-based models (referred to herein as “meal models”) of nutritional content of meals. This training is based on one or more datasets of images of meals in combination with “meal features” that describe various parameters of the meal. Examples of meal features include, but are not limited to, food type, meal contents, portion size, nutritional content (e.g., calories, vitamins, minerals, carbohydrates, protein, salt, etc.), food source (e.g., specific restaurants or restaurant chains, grocery stores, particular pre-packaged foods, school meals, meals prepared at home, etc.). Given the trained models, the Food Logger automatically provides estimates of nutritional information based on automated recognition of new images of meals provided by (or for) the user. This nutritional information is then used to enable a wide range of user-centric interactions relating to food consumed by individual users.

Abstract: A system and method to determine pulse transit time using a handheld device. The method includes generating an electrocardiogram (EKG) for a user of the handheld device. Two portions of the user's body are in contact with two contact points of the handheld device. The method also includes de-noising the EKG to identify a start time when a blood pulse leaves a heart of the user. The method further includes de-noising a plurality of video images of the user to identify a pressure wave indicating an arterial site and a time when the pressure wave appears. Additionally, the method includes determining the PTT based on the de-noised EKG and the de-noised video images.

Abstract: A wrist-worn device heart-monitoring device is presented. The wrist-worn heart-monitoring device includes a radial tonometer configured to output a pressure signal indicating a pulse pressure wave at a user's wrist, two or more electrodes configured to output an electrical signal indicating a user's heart has been commanded to contract, and a microphone configured to output an audio signal indicating a closing of a user's aortic valve. The wrist-worn heart-monitoring device further includes a pulse transit time monitor configured to calculate a pre-ejection period of the user's heart based on at least the pressure, electrical, and audio signals, and calculate a pulse transit time based on at least the pre-ejection period, the pressure signal, and the electrical signal.

Abstract: A system for transducing arterial pressure includes a one-piece flexible cap configured to fit around a flexible piezo-electric sensor that is configured to alter an internal resistance upon deflection. The flexible cap includes a deflection wall configured to deflect towards the flexible piezo-resistive sensor in proportion to pressure applied by the artery. A pressure-transducing medium is sealed between the one-piece flexible cap and the flexible piezo-resistive sensor, such that deflection of the deflection wall towards the flexible piezo-resistive sensor causes proportional deflection of the flexible piezo-resistive sensor.

Abstract: A wrist-worn pressure sensing device includes a pressure sensor. The wrist-worn pressure sensing device also includes a first strap that sets the position of the pressure sensor on a wearer's wrist and a second strap that engages with the first strap to adjust the overall length of the strap without moving the set position of the pressure sensor on the wearer's wrist.

Abstract: A first data window of a pulse waveform signal comprising a first number of samples is analyzed to determine a level of confidence that a pulse sensing device is placed correctly. If an initial level of confidence is met, the user is given positive feedback, and a second data window of a pulse waveform signal comprising a second, larger number of samples is analyzed. If an increased level of confidence is met, the user is given increased positive feedback. If a level of confidence is not met, the user is given negative feedback. If a final level of confidence is met, the user is given feedback that the pulse sensing device is placed correctly.

Abstract: A wearable sensing band is presented that generally provides a non-intrusive way to measure a person's cardiovascular vital signs including pulse transit time and pulse wave velocity. The band includes a strap with one or more primary electrocardiography (ECG) electrodes which are in contact with a first portion of the user's body, one or more secondary ECG electrodes, and one or more pulse pressure wave arrival (PPWA) sensors. The primary and secondary ECG electrodes detect an ECG signal whenever the secondary ECG electrodes make electrical contact with the second portion of the user's body, and the PPWA sensors sense an arrival of a pulse pressure wave to the first portion of the user's body from the user's heart. The ECG signal and PPWA sensor(s) readings are used to compute at least one of a pulse transit time (PTT) or a pulse wave velocity (PWV) of the user.

Abstract: The cardiovascular vital signs of a user are measured. One or more user activity metrics is received from one or more user activity sensors. A type of activity the user is currently engaged in is inferred from the received user activity metrics. Additional context that is associated with the inferred type of activity may also be identified. A determination is made as to if it is time to measure the cardiovascular vital signs of the user, where this determination is based on the inferred type of activity and may also be based on the identified additional context. Whenever it is determined to be time to measure the cardiovascular vital signs of the user, this measurement is made.

Abstract: Wearable pulse pressure wave sensing devices are presented that generally provide a non-intrusive way to measure a pulse pressure wave travelling through an artery using a wearable device. In one implementation, the device includes an array of pressure sensors disposed on a mounting structure which is attachable to a user on an area proximate to an underlying artery. Each of the pressure sensors is capable of being mechanically coupled to the skin of the user proximate to the underlying artery. In addition, there are one or more arterial location sensors disposed on the mounting structure which identify a location on the user's skin likely overlying the artery. A pulse pressure wave is then measured using the pressure sensor of the array closest to the identified location.

Abstract: A physical activity monitoring device includes a sensor array with one or more sensors configured to measure physical activity attributes of a user. A controller automatically determines time intervals where the user is actively engaged in a physical activity based on the physical activity attributes. The controller also automatically determines a type of physical activity the user in actively engaged in during the determined time intervals based on the physical activity attributes. A reporter outputs information regarding the type of physical activity to the user.