The present disclosure provides a grip sensor for quantifying pain experienced by a patient during spinal cord stimulation (SCS). The grip sensor includes an electronics enclosure, an annular outer shell substantially surrounding the electronics enclosure and sized to be held by the patient, a pressure sensor embedded in the outer shell and communicatively coupled to the electronics enclosure, the pressure sensor configured to measure a grip strength of the patient as SCS is applied to the patient, and a plurality of galvanic skin response sensors communicatively coupled to the electronics enclosure and configured to measure an electrical impedance of the skin of the patient as SCS is applied to the patient.

Disclosed are a system and method of detection of an interaction-error. The interaction-error is derived from an incorrect decision and is directed to interacting with a machine. During human-machine interaction, command related data values are obtained. Command related data values characterize any one of an interacting-command and an interacting-action. The command related data values are compared with command related reference data values, and an interaction-error is identified if a difference between the command related data values and the command related reference data values complies with a predefined criterion.

An external medical device includes monitoring circuitry configured to monitor a cardiac condition of a patient using the external medical device; and a controller configured to: receive at least one of patient input and non-patient user input of a patient's ability; determine a patient interaction mode of the external medical device based on the at least one of the patient input and the non-patient user input; and adapt the patient interaction mode of the external medical device over time based on the at least one of the patient input and the non-patient user input.

A force transducer is disclosed, which is arranged in such a way that, when a force is applied to the force transducer, two output signals from the force transducer are generated, which output signals are representative of the force components in a first plane and in a second plane perpendicular to the first plane, respectively, whereas force components in a third plane perpendicular to the first plane and the second plane do not affect the output signals from the force transducer. Furthermore, a measuring device is disclosed, comprising a handle comprising such a force transducer and a base unit, to which the handle is attached. Even further, a system for measuring muscle stiffness is disclosed, comprising a measuring unit and a processing unit, the measuring unit comprising such a measuring device.

Data regarding typing by a user may be collected and analyzed in order to assess one or more health conditions or functional states of the user. Each health condition that is assessed may be a disease or a symptom of a disease. For instance, based on the typing data, a computer may assess the presence, severity or probability of, or a change in, one or more symptoms such as: mild cognitive impairment; dementia; impairment of fine motor control; impairment of sensory-motor feedback; or behavioral impairment. A computer may calculate keystroke tensors that encode information about the typing. A computer may select or derive features from the keystroke tensors. These features may be fed into one or more machine learning algorithms, which in turn may output an assessment of a health condition or functional state of the user.

Method when a user performs a work task, wherein the user wears and uses a wearable, actively controlled piece of force-assisting equipment (110) used to assist the user in the performing of the said work task, which force-assisting equipment (110) comprises a force-exerting means (112,113) for assisting the user in applying a particular force and/or for performing movements of a particular type, and a sensor means (115) for sensing a force applied by the user, wherein an assisting force exerted by said force-exerting means (112,113) is feedback-controlled based on an instantaneous measurement value from the sensor means (115). The invention is characterised in that the method comprises the steps of during the performance of said work task, measuring said measurement value using the sensor means (115) for use in said feedback control; and using the measurement value to automatically calculate an actual ergonomic risk or load value for the performed work task using the said force-assisting equipment (110). The invention also relates to a system and a computer software product.

A grip assessment device includes a support structure having a periphery, a cover positioned around the support structure and configured to define a grip surface, and a plurality of sensor elements disposed along the periphery of the support structure, each respective sensor element of the plurality of sensor elements being configured to generate an output signal indicative of force applied to the grip surface at the respective sensor element. The plurality of sensor elements are distributed across the grip surface such that the output signals from the plurality of sensor elements are collectively indicative of a grip profile along the grip surface, the grip profile providing grip position data and grip magnitude data correlated with the grip position data.

A systems is provided herein to evaluate health of a patient. The system includes one or more testing modules configured to receive examination data related to at least one of gripping power, vision health, or hearing strength of a user; one or more pumps configured to provide fluid to or receive fluid from the user's body and analyze the fluid to determine one or more contents included in the fluid; a data processor unit configured to analyze the received examination data to determine whether the user is at risk of a health problem, and a communication unit capable of communicating information to a computing system. In response to determining that the user is at risk of the health problem, the data processor requests the communication unit to notify a health care provider about the risk. Corresponding methods and non-transitory computer readable medium are also disclosed.

A system for the integrated/functional detection of different measurements is described. The system comprises a part wearable by a driver of a vehicle and plurality of sensors integrated in the wearable part and configured to supply the following driver parameters: breathing parameters, heart parameters, perspiration parameters and of the pressure exerted on the vehicle driving wheel. The system also includes a processor for processing the driver parameters and correlating them to a driver psychophysical condition.

Described herein is a sensorized glove, in particular designed for ergonomic analysis, including an inner glove, which comprises a plurality of extensometer sensors configured for detecting relative movements between parts of a worker's hand; and an outer glove, which comprises a plurality of pressure sensors distributed over a palmar surface and configured for detecting the pressure exerted in corresponding areas of said palmar surface. Moreover described is a corresponding method for determining the type of grasp exerted by a worker.