An inertial measurement device includes: a first inertial sensor; a first inertial sensor module in which the first inertial sensor is stored in a first package made of resin; a base having a concave portion and made of ceramic; and a lid body. The first inertial sensor module is accommodated in an accommodation space between the base and the lid body and is hermetically sealed.

An inertial measurement device includes: a first inertial sensor; a first inertial sensor module in which the first inertial sensor is stored in a first package made of resin; a base having a concave portion and made of ceramic; and a lid body. The first inertial sensor module is accommodated in an accommodation space between the base and the lid body and is hermetically sealed.

An electronic device that enables identification of application of an impact is provided. The electronic device includes a module case including a first structure and a second structure having different deformation quantities, a first impact identification part formed between the first structure and the second structure and configured to generate a deformation according to the difference between the deformation quantities of the first and second structures at the time of applying the impact, and a second impact identification part that enables identification of whether the impact was applied based on the deformation of the first impact identification part.

A method of operation of a navigation system includes: calculating a speed difference value based on a sensor speed measurement and a location speed measurement; generating a speed probability distribution with the speed difference value and the sensor speed measurement calculating a density regression based on a speed density peak of the speed probability distribution; determining a speed adjustment factor from the density regression; and calculating an adjusted sensor speed from the sensor speed measurement with the speed adjustment factor.

Methods, systems and computer program products to detect distracted driving are disclosed. A mobile device is associated with a vehicle driver. Suspect activity associated with the vehicle driver is detected based at least in part on mobile device use data collected by the mobile device. A suspect activity record is generated comprising mobile device use data associated with the detected suspect activity. The suspect activity record and an identifier of the vehicle driver are provided to a repository.

Techniques are described for automated operations involving capturing and analyzing information from an interior of a house, building or other structure, for use in generating and providing a representation of that interior. Such techniques may include using a user's mobile device to capture visual data from multiple viewing locations (e.g., video captured while the mobile device is rotated for some or all of a full 360 degree rotation at each viewing location) within multiple rooms, capturing data linking the multiple viewing locations, analyzing each viewing location's visual data to create a panorama image from that viewing location, analyzing the linking data to determine relative positions/directions between at least some viewing locations, creating inter-panorama links in the panoramas to each of one or more other panoramas based on such determined positions/directions, and providing information to display multiple linked panorama images to represent the interior.

A method for calculating a tread frequency of a bicycle includes obtaining a first state of an acceleration signal in a first time window, determining a feature point set from the acceleration signal when the first state includes a riding state, where time distribution of a feature point in the feature point set meets a preset periodic distribution condition, and amplitude meets a physical rule, determining that the first state is the riding state when a feature point subset in the feature point set meets a preset reasonableness condition, and calculating, based on the feature point subset, a quantity of circles and a tread frequency that are in the first time window.

A method of operating a pre-opened pre-positioned clamp, the clamp being operable between an open and a closed position. The method comprises releasing the clamp from the open position using a tool head (201), making measurements of a movement of the tool head resulting from the releasing, recording data relating to the measurements, determining a frequency content of the data, and, on the basis of the determined frequency content, determining whether the clamp has moved to the closed position.

A system and method for monitoring performance of a repeated activity is described. The system comprises a motion sensing system and a processing system. The motion sensing system includes sensors configured to measure or track motions corresponding to a repeated activity. The processing system is configured to process motion data received from the motion sensing system to recognize and measure cycle durations in the repeated activity. In contrast to the conventional systems and methods, which may work for repeated activities having a high level of standardization, the system advantageously enables recognition and monitoring of cycle durations for a repeated activity, even when significant abnormal motions are present in each cycle. Thus, the system can be utilized in a significantly broader set of applications, compared conventional systems and methods.

A system and method for monitoring performance of a repeated activity is described. The system comprises a motion sensing system and a processing system. The motion sensing system includes sensors configured to measure or track motions corresponding to a repeated activity. The processing system is configured to process motion data received from the motion sensing system to recognize and measure cycle durations in the repeated activity. In contrast to the conventional systems and methods, which may work for repeated activities having a high level of standardization, the system advantageously enables recognition and monitoring of cycle durations for a repeated activity, even when significant abnormal motions are present in each cycle. Thus, the system can be utilized in a significantly broader set of applications, compared conventional systems and methods.