The present invention extends to methods, systems, and computer program products for providing a matching system for correlating accelerometer data to known movements. Data representing known movements can be obtained and stored in a database such as by processing and storing accelerometer data obtained from one or more accelerometers worn by a user while performing a particular movement. The accelerometer data obtained from a particular movement can be processed to generate a feature set descriptive of the accelerations associated with a particular movement or series of movements.

The present invention extends to methods, systems, and computer program products for providing a matching system for correlating accelerometer data to known movements. Data representing known movements can be obtained and stored in a database such as by processing and storing accelerometer data obtained from one or more accelerometers worn by a user while performing a particular movement. The accelerometer data obtained from a particular movement can be processed to generate a feature set descriptive of the accelerations associated with a particular movement or series of movements.

An acceleration sensor includes a circuit board with a recess that exposes a spring structure. The spring structure is formed from a material of the circuit board exposed by the recess and includes a vibrating element that is held in a resilient manner via at least one spring element. The sensor further includes a reference element connected rigidly to the circuit board and arranged at a distance from and opposite the vibrating element, an electrical circuit arranged on the vibrating element at a distance from the reference element, and at least one detection element. The circuit is configured to evaluate a signal that is configured to be influenced by a change in distance between the reference element and the at least one detection element in order to sense an acceleration of the acceleration sensor.

Systems and methods for filtering a micro-electromechanical system sensor rate signal with error feedback are provided. In one example, a micro-electromechanical system sensor rate signal is provided. Next, a feedback signal from a feedback loop is subtracted from the micro-electromechanical system sensor rate signal to produce a first combined signal. The first combined signal is then filtered to produce a filtered rate output. The micro-electromechanical system sensor rate signal is then subtracted from the filtered rate output to produce an error signal, wherein the error signal is used in the feedback loop to generate a feedback signal for a future time step.

Systems and methods for filtering a micro-electromechanical system sensor rate signal with error feedback are provided. In one example, a micro-electromechanical system sensor rate signal is provided. Next, a feedback signal from a feedback loop is subtracted from the micro-electromechanical system sensor rate signal to produce a first combined signal. The first combined signal is then filtered to produce a filtered rate output. The micro-electromechanical system sensor rate signal is then subtracted from the filtered rate output to produce an error signal, wherein the error signal is used in the feedback loop to generate a feedback signal for a future time step.

A tire longitudinal stiffness estimation system includes an electronic communication system disposed on a vehicle. A sensor is disposed on the vehicle in communication with the electronic communication system, and a processor is accessible through the electronic communication system. The sensor measures parameters associated with the vehicle and communicates data for the parameters to the processor. A mu slip curve generator receives the parameters to generate a mu slip curve in real time from the data. An extraction module extracts raw data from a linear portion of the mu slip curve. A denoising module de-noises the raw data from the mu slip curve by determining a vector for the raw data, an orientation of the vector, and a heading of the vector. The denoising module generates de-noised data, and a stiffness calculator receives the de-noised data and generates a longitudinal stiffness estimate for the tire.

A tire longitudinal stiffness estimation system includes an electronic communication system disposed on a vehicle. A sensor is disposed on the vehicle in communication with the electronic communication system, and a processor is accessible through the electronic communication system. The sensor measures parameters associated with the vehicle and communicates data for the parameters to the processor. A mu slip curve generator receives the parameters to generate a mu slip curve in real time from the data. An extraction module extracts raw data from a linear portion of the mu slip curve. A denoising module de-noises the raw data from the mu slip curve by determining a vector for the raw data, an orientation of the vector, and a heading of the vector. The denoising module generates de-noised data, and a stiffness calculator receives the de-noised data and generates a longitudinal stiffness estimate for the tire.

A vehicle collision warning prevention method includes the steps of: (a) extracting a forward video of a vehicle and video recognition information from a video recognition module mounted in a vehicle, and detecting a size change rate of a forward object included in the video recognition information at each frame of the forward video; (b) calculating an average OFCR of a predetermined frame section; (c) determining whether a value obtained by subtracting the average OFCR from a current OFCR is less than a predetermined threshold value; (d) determining that a brake operation signal is generated when it is determined that the value is less than the threshold value; (e) determining whether a collision warning signal is generated within a predetermined time after the step (d); and (f) preventing an output of the collision warning signal when the collision warning signal is generated at the step (e).

According to one embodiment, an apparatus comprising a portable monitoring device to be affixed to a user. The portable monitoring device including: 1) a set of one or more sensors to generate sensor data indicative of physical activity of a user when the portable monitoring device is affixed to the user; and 2) processing circuitry coupled with the set of sensors, to detect that the user has been sedentary for a period of time, and cause the portable monitoring device to alert the user responsive to the detection to encourage the user to move.

According to one embodiment, an apparatus comprising a portable monitoring device to be affixed to a user. The portable monitoring device including: 1) a set of one or more sensors to generate sensor data indicative of physical activity of a user when the portable monitoring device is affixed to the user; and 2) processing circuitry coupled with the set of sensors, to detect that the user has been sedentary for a period of time, and cause the portable monitoring device to alert the user responsive to the detection to encourage the user to move.