A smartphone or other mobile computer device, general purpose or specialized, wherein the smartphone device is configured to actively control the configuration of one or more bladders, compartments, chambers or internal sipes and one or more sensors located in either one or both of a sole or a removable inner sole insert of the footwear of the user and/or located in an apparatus worn or carried by the user, glued unto the user, or implanted in the user. The one or more bladders, compartments, chambers, or sipes, and one or more sensors are configured for computer control. A sole and/or a removable inner sole insert for footwear, including one or more bladders, compartments, chambers, internal sipes and sensors in the sole and/or in a removable insert; or on an insole; all being configured for control by a smartphone or other mobile computer device, general purpose or specialized.

An electronic device for gesture recognition, includes a processor operably connected to a transceiver. The transceiver is configured to transmit and receive signals for measuring range and speed. The processor is configured to transmit the signals, via the transceiver. in response to a determination that a triggering event occurred, the processor is configured to track movement of an object relative to the electronic device within a region of interest based on reflections of the signals received by the transceiver to identify range measurements and speed measurements associated with the object. The processor is also configured to identify features from the reflected signals, based on at least one of the range measurements and the speed measurements. The processor is further configured to identify a gesture based in part on the features from the reflected signals. Additionally, the processor is configured to perform an action indicated by the gesture.

A smartphone or other mobile computer device, general purpose or specialized, wherein the smartphone device is configured to actively control the configuration of one or more bladders, compartments, chambers or internal sipes and one or more sensors located in either one or both of a sole or a removable inner sole insert of the footwear of the user and/or located in an apparatus worn or carried by the user, glued unto the user, or implanted in the user. The one or more bladders, compartments, chambers, or sipes, and one or more sensors are configured for computer control. A sole and/or a removable inner sole insert for footwear, including one or more bladders, compartments, chambers, internal sipes and sensors in the sole and/or in a removable insert; or on an insole; all being configured for control by a smartphone or other mobile computer device, general purpose or specialized.

Systems for detecting when a person exhibits a smile with therapeutic benefits including a facial expression detection device and a system processor. The facial expression detection device is configured to acquire facial expression data. The system processor is in data communication with the facial expression detection device and is configured to execute stored computer executable system instructions. The computer executable system instructions include the steps of receiving facial expression parameter data establishing target facial expression criteria, receiving current facial expression data from the facial expression detection device, comparing the current facial expression data to the target facial expression criteria of the facial expression parameter data, and identifying whether the current facial expression data satisfies the target facial expression criteria. The target facial expression criteria define a smile with therapeutic benefits.

Methods and systems for imaging and analysis are described. Accurate pressure ulcer measurement is critical in assessing the effectiveness of treatment. However, the traditional measuring process is subjective. Each health care provider may measure the same wound differently, especially related to the depth of the wound. Even the same health care provider may obtain inconsistent measurements when measuring the same wound at different times. Also, the measuring process requires frequent contact with the wound, which increases risk of contamination or infection and can be uncomfortable for the patient. The present application describes a new automatic pressure ulcer monitoring system (PrUMS), which uses a tablet connected to a 3D scanner, to provide an objective, consistent, non-contact measurement method. The present disclosure combines color segmentation on 2D images and 3D surface gradients to automatically segment the wound region for advanced wound measurements.

A computer program and computer-based system for remotely determining a dental treatment plan (10) of a user (30) of a personal computing device (20) by obtaining, using the personal computing device (20), at least one digital image (1) of the person’s oral cavity (31) and additional non-image data (2) comprising a choice (7) of a predefined topic (5) by said user (30). The digital images (1) and non-image data (2) are processed to extract dental health indicators (8) that are used to evaluate any dental condition (9) of said user (30). A dental treatment plan (10) is generated based on the dental condition (9) and a database (3) defining logical relationships between predefined topics (5) and actions (6) for said user (30) to take, wherein a selection of said actions (6) arranged in a regimen and displayed on a user interface (25) of said personal computing device (20).

A method of, and system for, predicting conductive hearing loss risk in a person. The method includes utilizing, by using a processor, at least the following as inputs to a prediction model: (A) at least one first air conduction value for the person, and (B) any one of (a) a second air conduction value in noise for the person for in-phase binaural stimuli, or (b) a third air conduction value in noise for the person for antiphasic binaural stimuli. The method further includes predicting, by using the processor and an output of the prediction model, whether the person has a risk of conductive hearing loss. The method may be implemented without the need for bone conduction audiometry or any other clinical test to determine conductive hearing loss. The prediction model may be a logistic regression model.

Disclosed is a system for associating a symptom with a medical condition. The system comprises a server arrangement, associated with a user device. The server arrangement is operable to: provide, to user device, a set of user activities; receive, from user device, information relating to selection of a user activity from set of user activities; receive, from user device, user input associated with selected user activity; analyse user input and assign performance score thereto; identify, based on performance score, one or more symptoms; and assign severity score to symptom for associating symptom with medical condition. Disclosed also is method for associating symptom with medical condition and computer program product to execute aforementioned method.

A method for facilitating a Parkinson's Disease (“PD”) assessment of a patient includes capturing first video of a patient performing first test movements while holding the mobile device; capturing second video of the patient performing second test movements while maintaining the mobile device on their person; capturing third video of the patient performing third test movements including standing and walking; capturing one or more IMU readings using an IMU of the mobile device; processing the first video, the second video, and the third video according to (i) a hand landmark model to generate one or more hand biomarkers, (ii) a face landmark model to generate one or more face biomarkers, and (iii) a body landmark model to generate one or more body biomarkers; and determining an assessment score based on a standardized PD assessment by processing the biomarkers.

Electronic devices and methods are disclosed. First and second electronic devices include processors, which implement one or more methods, including receiving sensor data, determining an exercise starting timepoint based on first sensor data, estimating an exercise posture of a user based on second sensor data, estimating a pattern of change in distance between each of the plurality of external electronic devices, indicated by changes in the relative position between each the plurality of external electronic devices over a time period of the determined exercise starting timepoint, based on third sensor data, and generating exercise information based on the estimated exercise posture and the estimated pattern of change in distance between the plurality of external electronic devices.