A virtual scene interactive rehabilitation training robot based on a lower limb connecting rod model and force sense information and a control method thereof are disclosed. The thigh, calf and foot of a leg of a human body are equated to a three-connecting rod series-connected mechanical arm. A human body leg gravity compensation model is constructed. The leg posture of a patient is detected by Kinect. An interaction force between a limb of the patient and a rehabilitation robot is detected by a force sensor on the rehabilitation robot. Then, a progressive rehabilitation training method is designed for the model. According to a set weight reduction ratio, the motion of the rehabilitation robot is controlled by judging plantar force data.

A mobility augmentation system assists a user's movement by determining a corresponding electrical stimulation for the movement. A wearable stimulation array includes sensors, electrodes, an electrode multiplexer, and a controller that executes the mobility augmentation system. The sensors measure movement data, and the mobility augmentation system applies a movement model to the measured movement data. The model can determine different electrical actuation instructions depending on the movement stimulated. For example, to stimulate a knee flexion, the movement model output enables a first set of the electrodes to operate as cathodes and a second set of electrodes to operate as anodes. To stimulate a knee extension, the first set of electrodes can be enabled to operate as anodes and a third set of electrodes as cathodes. The user can provide feedback of the applied stimulation, which the system can use to retrain the model and optimize the stimulation to the user.

Aspects relate to a portable device that may be used to identify a critical intensity and an anaerobic work capacity of an individual. The device may utilize muscle oxygen sensor data, speed data, or power data. The device may utilize data from multiple exercise sessions, or may utilize data from a single exercise session. The device may additionally estimate a critical intensity from a previous race time input from a user.

Aspects relate to a portable device that may be used to identify a critical intensity and an anaerobic work capacity of an individual. The device may utilize muscle oxygen sensor data, speed data, or power data. The device may utilize data from multiple exercise sessions, or may utilize data from a single exercise session. The device may additionally estimate a critical intensity from a previous race time input from a user.

Electrode array for monitoring of physiological parameters and devices including or utilizing same, the electrode array including an active electrode configured to provide an electrical signal and at least two inactive electrodes configured to collect the electrical signal transferred from the active electrode, wherein each of the at least two inactive electrodes are positioned at a different predetermined distance from the active electrode.

Electrode array for monitoring of physiological parameters and devices including or utilizing same, the electrode array including an active electrode configured to provide an electrical signal and at least two inactive electrodes configured to collect the electrical signal transferred from the active electrode, wherein each of the at least two inactive electrodes are positioned at a different predetermined distance from the active electrode.

In some aspects, a device is disclosed for monitoring load bearing of a foot. The device can include a housing, a transmitter, and a pressure sensor. The housing can be positioned under a foot of a patient and attach to the foot. The transmitter can wirelessly transmit an indication that a portion of the foot is supporting at least a threshold weight. The pressure sensor can wake up from a sleep mode responsive to the portion supporting at least the threshold weight, cause the transmitter to transmit the indication, and return to the sleep mode.

Provided are a medical diagnosis apparatus and a medical diagnosis method using the same. According to an embodiment, the medical diagnosis apparatus may include: a main body; a chair unit movably supported by the main body and on which an object is positioned; a diagnosis part that is movably connected to the main body and is spaced apart from the chair unit by a preset first distance in one plane; a controller configured to generate a control signal for moving the diagnosis part according to preset information; and a first driving device configured to generate a driving force for moving the diagnosis part according to the control signal.

An apparatus and method for inspection of at least one of grass, artificial turf, infill, or dirt, on a surface, using optical photographic images from a camera and three-dimensional (“3D”) depth scans using the camera and one or more laser, to create a mask to distinguish aspects of the surface, so that the surface can be measured and analyzed.

A method for preoperatively characterizing an individual patients biomechanic function in preparation of implanting a prosthesis is provided. The method includes subjecting a patient to various activities, recording relative positions of anatomy during said various activities, measuring force environments responsive to said patient's anatomy and affected area during said various activities, characterizing the patient's biomechanic function from said relative positions and corresponding force environments, inputting the measured force environments, relative positions of knee anatomy, and patient's biomechanic function characterization into one or more computer simulation models, inputting a computer model of the prosthesis into said one or more computer simulation models, and manipulating the placement of the prosthesis in the computer simulation using said patient's biomechanic function characterization and said computer model of the prosthesis to approximate a preferred biomechanical fit of the prosthesis.