Abstract: In an embodiment, a method is described. The method comprises obtaining an indication of a speech pattern of a subject and using the indication to determine a predicted time of inspiration by the subject. A machine learning model is used for predicting the relationship between the speech pattern and a breathing pattern of the subject. The machine learning model can then be used to determine the predicted time of inspiration by the subject. The method further comprises controlling delivery of gas to the subject based on the predicted time of inspiration by the subject.

Abstract: An interface system for a user is provided that comprises an interface unit configured to engage and selectively apply a force on a lower jaw of the user. An actuating unit is configured to actuate the interface unit in order to selectively apply and adjust the force on the lower jaw. One or more sensors are configured to generate output signals conveying information related to sleep stages of the user during a sleep session. The interface system further comprises a processor configured to receive the output signals from the one or more sensors and determine a current sleep stage of the user. The processor controls the actuating unit based on the current sleep stage to adjust the force applied by the interface unit on the lower jaw.

Abstract: A two-phase recommendation system for a recommendation device, employing both an external recommendation process and an internal, to a recommendation device, recommendation process. In particular, a processing unit uses a first data file, which is modifiable by an external source, and a second data file stored in a memory unit to recommend one or more content items to a user. The first and second data files are stored in a memory unit of the recommendation device.

Abstract: According to an embodiment of an aspect, there is provided a computer-implemented method for determining a sleep state of a user. The method comprising receiving (S11) a physiological signal from a physiological signal detector used by the user. The method further comprising determining (S12), based on the received physiological signal, the sleep state of the user. The method further comprising calculating (S13) a reliability value associated with the determination. The reliability value being calculated based on a comparison of the received physiological signal with historic physiological signals of the same sleep state as the determined sleep state. There is further provided a device (20) and computer-readable medium (30). In accordance with the present disclosure, the sleep state of a user may be determined with greater accuracy when compared with past methods.

Abstract: In an embodiment, an apparatus (16) is presented that classifies device-sensed movement along a path based on a score that characterizes a geometrical property of the movement.

Abstract: A method and system for modifying a prediction model. In particular, an inaccuracy of the prediction model is categorized into one of at least three categories. Different modifications are made to the prediction model depending on the category of the inaccuracy. In particular examples, an inaccuracy category defines what training data is used to modify the prediction model.

Abstract: A system for managing a call includes a virtual caregiver that assists callers of a monitoring service in response to data received from a monitoring device. The virtual caregiver includes conversation analyzer that initiates a call to a user of the monitoring device and performs a conversation with the user during the call. The conversation is performed by generating audible comments in a synthesized voice to interact with the user. The audible comments are generated to elicit voice responses from the user containing information corresponding to the sensor data. The conversation analyzer also analyzes audible features of the voice responses using one or more models to interpret a condition of the user, generates a decision based on the interpreted condition of the user, and performs at least one action based on the decision.

Abstract: In an embodiment, an apparatus (16) is presented that classifies device-sensed movement along a path based on a score that characterizes a geometrical property of the movement.

Abstract: In an embodiment, a method is described. The method comprises obtaining an indication of a speech pattern of a subject and using the indication to determine a predicted time of inspiration by the subject. A machine learning model is used for predicting the relationship between the speech pattern and a breathing pattern of the subject. The machine learning model can then be used to determine the predicted time of inspiration by the subject. The method further comprises controlling delivery of gas to the subject based on the predicted time of inspiration by the subject.

Abstract: An audio processing apparatus includes a receiver configured to receive audio data including audio components and render configuration data including audio transducer position data for a set of audio transducers. A renderer is configured to generate audio transducer signals for the set of audio transducers from the audio data, and to render audio components in accordance with rendering modes. A render controller is configured to select a rendering mode for the renderer based on the audio transducer position data. The renderer is configured to employ different rendering modes for different subsets of the set of audio transducers and the render controller is configured to independently select rendering modes for each of the different subsets of the set of audio transducer including selecting the rendering mode for a first audio transducer in response to a position of the first audio transducer relative to a predetermined position for the first audio transducer.

Abstract: In an embodiment, a wearable device (12) is disclosed that automates the detection and determination of a type of activity, and both measures physiological and behavioral parameters and computes information corresponding to measured physiological parameters based on the determined type of activity. An embodiment of the wearable device provides these features by wirelessly receiving a signal with information coded therein that enables the wearable device to automatically detect and identify the type of activity in which a person (82) is engaged. The determination of the type of activity enables a more accurate computation of information that is specific to the activity in which the person is engaged, the computation of information based on the measured physiological and behavioral parameter.

Abstract: In an embodiment, a system is disclosed that receives a plurality of data structures that comprise contextually-related notifications, associates the data structures to starting, intermediate, and ending nodes, establishes plural possible pathways from the starting and intermediate nodes, each of the starting and intermediate nodes comprising a statement table with plural statements (and hence paths) to choose from based on measures, and based on continual input data and computation of the measures of each statement table, adding nodes to link to a selected starting node and then other nodes to ultimately provide a chain of notifications presented in non-overlapping time intervals and in narrative form that provide an indication of progress in advancing a user towards a goal.

Abstract: An audio apparatus includes a receiver configured to receive audio data and audio transducer position data for a plurality of audio transducers; and a renderer configured to render the audio data by generating audio transducer drive signals for the audio transducers from the audio data. Further, a clusterer is configured to cluster the audio transducers into a set of clusters in response to the audio transducer position data and to distances between audio transducers in accordance with a distance metric. A render controller is configured to adapt the rendering in response to the clustering. The apparatus is configured to select array processing techniques for specific subsets that contain audio transducers that are sufficiently close and allow automatic adaptation to audio transducer configurations thereby, e.g., allowing a user increased flexibility in positioning loudspeakers.

Abstract: In an embodiment, an apparatus (36) is presented that establishes a cost to the subject in performing physical activity during time segments of plural types of subject behavior for one or more days of his or her daily routine and simulates scenarios that are used to provide a health plan (110) that best changes a physiological parameter over a projected period of time while minimizing a total cost to the subject.

Abstract: A system and methods for automatically commissioning electrical fixtures using sound are disclosed. Electrical fixtures (140-149) detect sounds produced by a sound generator moved along a path (300) through installed fixtures according to a building plan (100). Each electrical fixture may be associated with a mapped fixture location in the building plan by correlating the detected sound with the location of the sound generator along the path.

Abstract: An audio processing apparatus comprises a receiver (705) which receives audio data including audio components and render configuration data including audio transducer position data for a set of audio transducers (703). A renderer (707) generating audio transducer signals for the set of audio transducers from the audio data. The renderer (7010) is capable of rendering audio components in accordance with a plurality of rendering modes. A render controller (709) selects the rendering modes for the renderer (707) from the plurality of rendering modes based on the audio transducer position data. The renderer (707) can employ different rendering modes for different subsets of the set of audio transducers the render controller (709) can independently select rendering modes for each of the different subsets of the set of audio transducers (703).

Abstract: An audio apparatus comprises a receiver (605) for receiving audio data and audio transducer position data for a plurality of audio transducers (603). A renderer (607) renders the audio data by generating audio transducer drive signals for the audio transducers (603) from the audio data. Furthermore, a clusterer (609) clusters the audio transducers into a set of clusters in response to the audio transducer position data and to distances between audio transducers in accordance with a distance metric. A render controller (611) adapts the rendering in response to the clustering. The apparatus may for example select array processing techniques for specific subsets that contain audio transducers that are sufficiently close. The approach may allow automatic adaptation to audio transducer configurations thereby e.g. allowing a user increased flexibility in positioning loudspeakers.

Abstract: A system and methods for automatically commissioning electrical fixtures using sound are disclosed. Electrical fixtures (140-149) detect sounds produced by a sound generator moved along a path (300) through installed fixtures according to a building plan (100). Each electrical fixture may be associated with a mapped fixture location in the building plan by correlating the detected sound with the location of the sound generator along the path.