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 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 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: 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: 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: 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: 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: The present invention relates to a device, system and method for reliable and fast fall detection. The device comprises a sensor input (11) for obtaining sensor data related to movement of a subject acquired by a body-worn sensor (20, 22, 61) worn by the subject, and a video input (12) for obtaining video data of the subject and/or the subject's environment. An analysis unit (13) analyzes the obtained sensor data to detect one or more signal features indicative of a potential fall of the subject and for analyzing, if one or more such signal features have been detected, the detected one or more signal features and/or related sensor data in combination with related video data to identify similarities between: changes of the related sensor data and/or the signal features over time; and changes of the video data over time. An output (14, 64, 65, 66) issues a fall detection indication if the level and/or amount of detected similarities exceeds a corresponding threshold.

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 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 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 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 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: Techniques described herein relate to applying reinforcement learning to improve engagement with counseling chatbots. In various embodiments, based on a first state of a subject and a decision model (109), a given natural language response may be selected (404) from a plurality of candidate natural language responses and provided to the user by the counseling chatbot. A free-form natural language input may be received (408) from the subject at one or more input components of one or more computing devices. A second state of the subject may be determined (410) based on speech recognition output generated from the free-from natural language input. The second state may be a positive, negative, or neutral valance towards a target behavior change. Based on the second state, and instant reward may be calculated (412) and used to train (414) the decision model.

Abstract: The present invention relates to a device, system and method for reliable and fast fall detection. The device comprises a sensor input (11) for obtaining sensor data related to movement of a subject acquired by a body-worn sensor (20, 22, 61) worn by the subject, and a video input (12) for obtaining video data of the subject and/or the subject's environment. An analysis unit (13) analyzes the obtained sensor data to detect one or more signal features indicative of a potential fall of the subject and for analyzing, if one or more such signal features have been detected, the detected one or more signal features and/or related sensor data in combination with related video data to identify similarities between: changes of the related sensor data and/or the signal features over time; and changes of the video data over time. An output (14, 64, 65, 66) issues a fall detection indication if the level and/or amount of detected similarities exceeds a corresponding threshold.

Abstract: The present disclosure pertains to a method and system configured for generating one or more statements. In some embodiments, the system comprises at least one processor; memory operatively connected with the at least one processor; a communication component operatively connected to the at least one processor and configured to communicate with a user device via a network. The at least one processor is configure by machine-readable instructions to receive one or more measurements pertaining to a parameter of a user from the user device; generate one or more statements based on the one or more measurements and one or more templates; and transmit, via the network, the one or more statements for presentation on the user device.