Abstract:
A user input detector for a mobile device is described having an ultrasound demodulator having an input for receiving an ultrasound signal reflected from a user and an output for outputting a demodulated ultrasound signal; a gesture processor comprising: a time-frequency processing module configured to generate a time-varying ultrasound-image spectrum from the demodulated ultrasound signal; an image-feature extraction module configured to extract micro-doppler features from the time-varying ultrasound image spectrum; a feature selection module configured to select and compress the extracted micro-doppler features; and a gesture detection module configured to compare the selected micro-doppler features with a known feature set and to output a detected gesture based on the comparison. The user input detector may be incorporated into a mobile phone for example to provide an always on low power control mechanism for the mobile phone by recognizing user gestures and executing control commands in response to those user gestures.
Abstract:
A system and a method for determining one or more wave characteristics from a moving platform are disclosed. A sonar system, such as an Acoustic Doppler Current Profiler, can profile the water motion relative to the platform, and an earth reference can determine a measure of the platform motion relative to a fixed earth reference. Both water profile and earth reference measurements can be synergistically employed to compensate for motion of the platform. Directional wave spectra and non-directional wave spectrum can be computed and translated via linear wave theory to surface height spectra and used to calculate characteristics, such as significant wave height, peak period, and peak direction.
Abstract:
A radio user equipment (UE) mobility status is determined in a communications node. UE mobility status measurements associated with the UE communicating over a radio channel are performed. The UE mobility status corresponds to a degree of variation of the radio channel over time. Channel characteristics of the radio channel at a first time and at a second later time are determined. Based on the determined channel characteristics, a channel characteristic error metric is determined and compared to a predetermined threshold. The UE mobility status is determined based on one or more iterations of the threshold comparison.
Abstract:
The invention relates to a method of cardiac monitoring, comprising (a) aiming, with a low angular precision, a non-imaging sensor at said heart to receive a signal from said heart; (b) automatically identifying a spatially specific tissue in said heart by said sensor based on a signature pattern in said received signal; (c) extracting of a value of a cardiac parameter associated with said specific tissue using a signal detected by said sensor; (d) continuing cardiac monitoring by (i) receiving a further signal from said specific tissue; (ii) identifying said specific tissue in said further signal; and (iii) extracting a further value of said cardiac parameter from a signal detected by said sensor; and (e) repeating (d) for at least 10 minutes.
Abstract:
A time difference between two similar but time-shifted signals is determined using a difference function. For example, similar but time-shifted first and second signals are sampled to generate a. discrete mathematical function whose discrete sample points define overlapping ranges. Typically, at least one of the multiple overlapping ranges defined by sample points of the discrete mathematical function can be used to interpolate a time difference between the first and second signals.
Abstract:
A longitudinal area (3, 2) of a vessel (30, 40) in a body is scanned using a color Doppler imaging method, such that an imaging plane is formed approximately through the center of said vessel. A number of color pixels in a scanned cross section of the vessel in which volume flow is detected are counted and tabulated. From this number of pixels, an observed cross-sectional area of the vessel is determined. Frequency shift information for each of the counted pixels is determined and these frequency shifts are spatially averaged. The instantaneous volume flow through the vessel is then computed from the cross-sectional area and frequency shift information. The volume flow for several different samples is computed. The instantaneous volume flows from each color Doppler imaging frame are temporally-averaged over one or more integral cardiac cycles to compute a temporally-averaged volume flow. Also a three-dimensional imaging measurement may be used.
Abstract:
A technique for continuously determining and displaying the peak velocities of spectral Doppler information is disclosed. A Doppler noise threshold level is determined from operating characteristics of the ultrasound system, probe, or both. Received spectral Doppler data for a spectral line is compared to this threshold to identify a valid peak velocity value. Spectral lines are examined in advance of their display to detect excursions due to artifacts such as valve clicks. Peak velocity values are interpolated and displayed in place of artifact peak values. Individual heart cycles over which quantified measures of cardiovascular performance are computed and displayed are selected by the R-wave intervals of an ECG trace. The interval of the concurrent spectral Doppler display corresponding to the heart cycle interval over which the quantified measures are computed or pertain is automatically highlighted for the user.