A system is disclosed herein for providing a kinetic assessment and preparation of a prosthetic joint comprising one or more prosthetic components. The system comprises a prosthetic component including sensors and circuitry configured to measure load, position of load on a curved surface, joint stability, range of motion, and impingement. In one embodiment, the system is for a ball and socket joint of a musculoskeletal system. The system further includes a computer having a display configured to graphical display quantitative measurement data to support rapid assimilation of the information. The kinetic assessment measures joint alignment under loading that will be similar to that of a final joint installation. The kinetic assessment can use trial or permanent prosthetic components. Furthermore, adjustments can be made to the applied load magnitude, position of load, and joint alignment by various means to fine-tune an installation.

Disclosed is an apparatus for estimating bio-information. The apparatus for estimating bio-information includes: a sensor part comprising a pulse wave sensor array configured to detect a pulse wave signal when an object contacts a contact surface of the sensor part, and a load sensor configured to detect a first contact load applied by the object to the contact surface; and a processor configured to obtain contact load distribution of the contact surface based on the pulse wave signal, and to estimate bio-information based on the contact load distribution.

A load sensing device for a shoe includes a base element having a first side and an opposite second side. The first side has a predefined area. A first load sensing element and a second load sensing element are positioned at the first side of the base element. The first load sensing element is positioned in a first area of the predefined area of the first side, and the second load sensing element is positioned in a second area of the predefined area of the first side. The first load sensing element has a fixed position relative to the second load sensing element during use. The first load sensing element and the second load sensing element are configured to measure a load applied to at least part of the predefined area of the first side.

Devices and methods for determining item-specific information for single or multiple items on one or multiple substrates are described. The method includes generating multiple sensor multiple dimensions array (MSMDA) data from multiple sensors, where each of the multiple sensors capture sensor data for one or more items in relation to a substrate. For each item, the method includes determining relationships between the multiple sensors based on characteristics of the MSMDA data, determining a location of the item on the substrate based on at least the determined relationships between the multiple sensors, determining an angular orientation of the item on the substrate based on at least the determined relationships between the multiple sensors, and determining a body position of the subject on the substrate based at least the determined relationships between the multiple sensors, the location of the subject, and the angular orientation of the item.

An apparatus includes a base portion configured to selectively couple with a robotic arm. A shaft extends distally form the base portion and terminates into a distal end. A sleeve is slidably coupled to the shaft. A colpotomy cup is fixedly secured to a portion of the sleeve. One or more sensors are configured to detect a force applied to the sleeve, the shaft, or both the sleeve and the shaft.

A system for assessment of neurocognitive and neuromotor control performance, the system comprising a portable force plate configured to collect force plate data indicative of movement and postural control of a subject as the subject performs a task, a depth sensing device configured to, simultaneously with the collection of the force plate data, collect depth data of the subject as the subject performs the task, an interface board configured to, simultaneously with the collection of the force plate data and the collection of the depth data, generate stimuli to instruct the subject to perform a particular task and to generate interface board data indication of input received from the subject in response to the stimuli, and a computer-based controller configured to execute one or more neurocognitive and neuromotor control performance assessment program to analyze the force plate data, the depth data, and the interface board data.

A patient support apparatus comprises a plurality of load cells, a frame supported on the load cells, a mattress, a vibration sensor, and a control system. The mattress includes a plurality of inflatable zones positioned on the frame, the mattress and frame cooperating to direct any patient load through the mattress and frame to the load cells. The control system includes a controller operable to receive a separate signal from each of the plurality of load cells and the vibration sensor and process the signals to identify motion of the patient.

A technology is described for determining an intended movement from neuromuscular signals. An example method (800) includes receiving electromyography (EMG) data corresponding to single-ended channels of an electrode array (810), where EMG signals are detected by electrodes comprising the single-ended channels of the electrode array and the EMG signals are converted to the EMG data. Determining differential channel pairs for the single-ended channels of the electrode array (820) and extracting feature data from the EMG data of the differential channel pairs (830). Thereafter a feature data set is selected from the feature data of the differential channel pairs (840) and the feature data set is input to a decode model configured to correlate the feature data set to an intended movement (850). Decode output is received from the decode model indicating the intended movement (860) and the decode output is provided to a device (870).

Methods and systems are provided for obtaining cleaned sequences showing trajectories of movement of a center of gravity and for estimating a biometric information pattern or value of a target. One of the methods includes removing noises from initial sequences showing trajectories of movement of a center of gravity to obtain the cleaned sequences. Another one of the methods includes reading cleaned sequences of the target into a memory, extracting features from the cleaned sequences, and estimating a biometric information pattern or value of the target from the extracted features, using a classification or regression model of biometric information patterns or values. The biometric information pattern may be a pattern derived from respiratory or circulatory organs of a target.

A patient transport apparatus comprises support structure. The support structure comprises a base, a support frame, and a patient support deck. A headboard and a footboard are coupled to the support structure. The support frame comprises a head section and a body section, the body section coupled to the patient support deck. The patient support deck comprises a patient support surface capable of articulating relative to the support frame. The head section is movable relative to the body section to define first and second configurations of the support frame, the support frame having a first footprint in the first configuration and a second footprint, smaller than the first footprint, in the second configuration.