A method of evaluating rehabilitation potential in patients experiencing painful musculoskeletal or neuropathic conditions or both, by maximizing multidimensional rehabilitation outcomes by better identifying the specific needs of each patient; understanding the many obstacles to rehabilitation success falling into motivational, physical, and emotional categories; physical obstacles to rehabilitation including but not limited to incorrect diagnoses and deconditioning; emotional obstacles including fear avoidance, catastrophizing, generalized anxiety, depression, childhood adverse events, emotional awareness deficits; and motivational obstacles including factitious disorder, personality disorders, malingering and apathy. The resulting comprehensive pain rehabilitation program combines multiple treatment options. Medicinal treatments include anti-inflammatory medications; muscle relaxants; opioids and cannabinoids; injection therapies; neuropathic medications; and pain adjuvant medications. Mental health services include mindfulness, biofeedback, progressive relaxation, cognitive behavioral therapies, logotherapy, and trauma therapies. Physical rehabilitation services include physical or occupational therapy; chiropractic; massage therapy; acupuncture; osteopathy and personalized exercises.

The present invention relates to detecting impairment. Impairment is generally systemic and may impact all regions of the body, including muscle responses and cognitive responses. An inverse relationship typically exists between involuntary muscle reaction time to a stimulus and level of impairment. Reaction time is impacted by many intoxicants, as well as by one or more medical conditions. In preferred form, a video records an involuntary response to a stimulus such as a flash of light, a loud sound, touch or an electrical stimulation. Software is utilized to deliver the stimulus, acquire, analyze, and output the reaction time and/or magnitude of the subject. Classification of the degree of impairment is then determined, e.g., using of comparative datasets and/or algorithms.

A hot/cold sensation estimating device according to one embodiment includes a sensing unit and an estimating unit. The sensing unit is configured to sense a behavioral thermoregulatory reaction and an autonomic thermoregulatory reaction of living matter against an ambient environment based on sensor data acquired through a sensor for sensing vital activities of the living matter. The estimating unit is configured to estimate a hot/cold sensation sensed by the living matter based on a sensing result of the behavioral thermoregulatory reaction and a sensing result of the autonomic thermoregulatory reaction.

Systems and methods for remote therapy and patient monitoring are provided. A method comprises contacting an outer skin surface of a patient with a contact surface of a stimulator and transmitting an electrical impulse from the stimulator transcutaneously through the outer skin surface to a nerve within the patient. Data related to parameters of the electrical impulse applied to the nerve is stored and transmitted to a remote source. The data may include duration of treatment, amplitude of the electrical impulse, compliance with a prescribed therapy regimen or other relevant data related to the therapy. The method may further include collecting patient status data, such as symptoms of a medical condition (e.g., severity of a headache) before, during and/or after stimulation. The patient status data is correlated with the treatment data to monitor compliance and/or the effectiveness of the therapy.

The present disclosure enables personalized cardiac rehabilitation guidance and care continuum using a personalized cardiovascular hemodynamic model that effectively simulates cardiac parameters when the patient performs an activity using a wearable device like a digital watch that can help capture Electrocardiogram (ECG) signal, Photoplethysmogram (PPG) signal and accelerometer signal. The cardiovascular hemodynamic models of the art are not personalized and cannot be input with real time parameters from the subject being monitored. Input parameters including Systemic Vascular Resistance (SVR) using Metabolic EquivalenT (MET) levels associated with an activity level of the subject, unstressed blood volume using an autoregulation method, total blood volume in a body of the subject, and heart rate of the subject are estimated and input to the personalized cardiovascular hemodynamic model to estimate cardiac parameters including cardiac output, ejection fraction and mean arterial pressure.

A system and method for training program generation and modification of that program based on assessed functional state and/or workload performance. User-interface logic preferably operating on a mobile device permits a user to record bio-signals indicative of functional state. Assessment-adjustment logic, that may be located at a distance, conducts body system assessments from the received bio-signal data and produces training session targets based on the current functional state of the user. User training objective data may be input through the user-interface logic. Workload performance may be monitored and the training session targets modified based on measured past performance to improve future performance. Various embodiments are disclosed.

A physiological information processing apparatus includes a processor and a memory storing computer-readable instructions. When the computer-readable instructions are executed by the processor, the apparatus obtains physiological information data indicative of physiological information of a subject, obtains RR interval data including a plurality of RR intervals based on the physiological information data, identifies an RR interval indicative of arrhythmia, and displays the RR interval data as plotted points on a two-dimensional coordinate system having one axis representing an n-th RR interval and another axis representing an (n+1)-th RR interval. The RR interval data is displayed on the two-dimensional coordinate system such that a visual mode of a plurality of first plotted points associated with the RR interval indicative of arrhythmia and a visual mode of plotted points of the RR interval data other than the plurality of first plotted points are different from each other.

A brain function measurement device (100) includes a brain blood flow information acquirer (1) configured to acquire brain blood flow information (d1) of a subject (P), a rest information acquirer (2) configured to acquire rest information (d5) to determine whether or not the subject is at rest, and a controller (3) configured to acquire, as resting measurement data (d2), the brain blood flow information with the rest information satisfying a predetermined condition based on the rest information acquired by the rest information acquirer.

Systems and methods for remote therapy and patient monitoring are provided. A method comprises contacting an outer skin surface of a patient with a contact surface of a stimulator and transmitting an electrical impulse from the stimulator transcutaneously through the outer skin surface to a nerve within the patient. Data related to parameters of the electrical impulse applied to the nerve is stored and transmitted to a remote source. The data may include duration of treatment, amplitude of the electrical impulse, compliance with a prescribed therapy regimen or other relevant data related to the therapy. The method may further include collecting patient status data, such as symptoms of a medical condition (e.g., severity of a headache) before, during and/or after stimulation. The patient status data is correlated with the treatment data to monitor compliance and/or the effectiveness of the therapy.

An information processing apparatus according to the present technology includes a processing section that executes a process including a correction process of specifying noise included in perspiration data acquired by a perspiration sensor on a basis of sensor data acquired by a different type of sensor than the perspiration sensor, and removing the noise from the perspiration data. According to such a technology, noise estimated according to other sensor data can be removed from the perspiration data, making it possible to maintain high accuracy in a later process of estimating activity in the autonomic nerves.