This disclosure relates to a method and system for diagnosing the extent of degeneration of a knee joint, and determining a suitable prosthesis for use in knee arthroplasty as indicated by the extent of joint degeneration. According to the disclosure there is provided a method of determining a corrective surgical procedure for the treatment of degeneration of a joint, including the steps of comparing a set of radiological images, and in particular a set of x-ray images of the joint, to a set of degenerative joint conditions to determine a diagnosis; and correlating the diagnosis with a grading system which prescribes a corrective surgical procedure. The prescribed procedure may be a total knee arthroplasty, a partial knee arthroplasty, a patellofemoral arthroplasty or an anterior cruciate ligament reconstruction.

System and method for measuring diabetes mellitus condition of a subject is disclosed. The disclosed system and method includes thermal sensors for capturing thermal images and/or videos of a body part; and a processing engine to detect a predefined region of the body part in each frame of the captured images and/or videos. The processing engine segments one or more portions from the detected predefined region in each frame of the captured images and/or videos to identify a region of interest comprising major arteries in the segmented portions. Based on the ROI, the engine extracts pixel values, representing biosignals, from each frame of the captured images and/or videos so as to determine one or more parameters associated with the hemodynamic factors and a rate of atherosclerosis of the subject. Further, a risk score for the diabetes mellitus condition based on the determined parameters using computational models is measured.

The present invention describes methods and systems to enable a concerned party to continuously monitor the progression of a medical condition in one or more patients. The progression of the medical condition is determined by processing sensor data obtained from one or more physiological and/or motion sensors and survey data obtained from the patients. Further, environmental data such as air quality, temperature and humidity may also be used along with the sensor data and the survey data to monitor/track the progression of the medical condition.

Described are systems and methods for administration of nitric oxide (NO) with use of left ventricular assists devices (LVADs), as well as systems and methods for monitoring the NO delivery devices and/or the LVAD.

The present disclosure provides methods of identifying a patient in need of pressure ulcer treatment and treating the patient with clinical intervention selected based on sub-epidermal moisture values. The present disclosure also provides methods of stratifying groups of patients based on pressure ulcer risks and methods of reducing incidence of pressure ulcers in a care facility.

The exemplified methods and systems facilitate one or more dynamical analyses that can characterize and identify synchronicity between acquired cardiac signals and photoplethysmographic signals to predict/estimate presence, non-presence, localization, and/or severity of abnormal cardiovascular conditions or disease, including, for example, but not limited to, coronary artery disease, heart failure (including but not limited to indicators of disease or conduction such as abnormal left ventricular end-diastolic pressure disease), and pulmonary hypertension, among others. In some embodiments, statistical properties of the synchronicity between cardiac signals and photoplethysmographic signals are evaluated. In some embodiments, statistical properties of histogram of synchronicity between cardiac signals and photoplethysmographic signals are evaluated. In some embodiments, statistical and/or geometric properties of Poincaré map of synchronicity between cardiac signals and photoplethysmographic signals are evaluated.

Methods and systems are disclosed for evaluating a neurological condition by employing at least one motion sensor, configured to be attached to a body appendage, a memory associated with the sensor(s) to periodically record movement data during periods of prescribed exercises; and a processor for analyzing changes in movement data over time to evaluate the progression of the neurological condition. In one embodiment, the neurological condition is ALS and at least four motion sensors are employed such that each arm and leg of the patient has an associated sensor. The sensors can be accelerometers that measure the displacement, velocity and acceleration of an associated limb during periods of prescribed exercise. For example, changes in the patient's ability to repeat a series of limb-lifting exercises or the measurement of limb tremors associated with the conduct of the exercises can be correlated with norms and analyzed to classify the stage of ALS in a patient and/or predict the rate of progression.

A pressure ulcer detection system includes a support surface assembly including a transparent window, a signal generator/receiver, and an optical fiber embedded at least in part in the support surface assembly. The fiber conveys outgoing radiation from the signal generator/receiver to the window thereby illuminating a tissue site which overlies the window and conveys incoming radiation reflected from the tissue site and through the window back to the generator/receiver. The system also includes a controller in communication with the signal generator/receiver. The controller comprises a processor adapted to assess health status of tissue at the tissue site based on a property of at least one of the outgoing radiation and the incoming radiation, and to communicate an outcome of the assessment to a destination.

A pain management treatment protocol which assesses a patient's pain and related factors to susceptibility of opioid abuse, which evaluates a patient's capacity for pain treatments under multiple disciplines, and which further provides a rating for the administrating professional to apply the appropriate treatment.

An electronic system is provided that simulates a glucose-insulin metabolic system of a T2DM or prediabetic subject, wherein the system includes a subsystem that models dynamic glucose concentration in a T2DM or prediabetic subject, including an electronic module that models endogenous glucose production (EGP(t)), or meal glucose rate of appearance (Ra(t>>, or glucose utilization (U(t)), or renal excretion of glucose (B(t)), a subsystem that models dynamic insulin concentration in said T2DM or prediabetic subject, including an electronic module that models insulin secretion (S(t)), an electronic database containing a population of virtual T2DM or prediabetic subjects, each virtual subject having a plurality of metabolic parameters, and a processing module that calculates an effect of variation of at least one metabolic parameter value on the glucose insulin metabolic system of a virtual subject by inputting the plurality of metabolic parameter values.