A device and method are provided for treating a patient with vibration and/or tactile and/or thermal stimuli. The device includes first and second stimulating units for generating first and second stimuli respectively. The stimuli are vibration and/or tactile and/or thermal stimuli, and each of the stimuli is repeated on average at a frequency of 1 to 60 Hz. The stimuli are generated partly at different times.

A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan, a patient interface comprising an output device configured to present telemedicine information associated with a telemedicine session, and a first computing device configured to: receive treatment data pertaining to the user while the user uses the treatment device to perform the treatment plan; identify at least one aspect of the at least one measurement pertaining to the user associated with a first treatment device mode of the treatment device; determine whether the at least one aspect of the measurement correlates with a secondary condition of the user; and, in response to a determination that the at least one aspect of the at least one measurement is correlated with the at least one secondary condition of the user, generate secondary condition information indicating at least the secondary condition.

An example method includes administering a treatment to a subject during a time interval. The example method further includes receiving, from an external device, a first signal indicating a physiological parameter of the subject detected during the time interval; removing, from the physiological parameter, an artifact associated with the treatment; and in response to removing the artifact from the physiological parameter, outputting a second signal indicating the physiological parameter.

A walking assistance method may include: computing an amount of exercise of a user based on a biosignal of the user; adjusting a pattern of an assist parameter based on the amount of exercise; and/or generating a force corresponding to the amount of exercise, based on the adjusted pattern. A walking assistance apparatus may include: a pattern adjuster configured to compute an amount of exercise of a user based on a biosignal of the user; and/or a driver configured to generate a force corresponding to the amount of exercise based on a pattern of an assist parameter based on the amount of exercise.

A medical system for assisting with an intubation procedure for a patient. The system comprising airflow sensors configured to obtain data indicative of airflow in the patient's airway and physiological sensors configured to obtain information regarding airflow in the patient's lungs. The system further including a monitoring device communicatively coupled to the airflow sensors and the physiological sensors. The patient monitoring device comprising at least one processor coupled to memory and configured to: provide a user interface on a display and assist the rescuer in determining proper placement of an endotracheal tube, receive the data indicative of the airflow in the patient's airway, receive the physiological information regarding the airflow in the patient's lungs, and determine whether the tube is properly placed based on the received physiological information, and present an output of the determination of whether the ET tube was properly placed.

Systems and methods are provided for controlling infrared radiation (IR) sources of a sauna including tuning IR wavelength-ranges and radiated power-levels of IR sources, and directing IR to locations on a user's body. In one illustrative embodiment, a sauna may be provided having adjustable heat sources to emit IR at any wavelength resulting in a desirable radiation treatment for the sauna user. In another illustrative embodiment, a method is provided for tuning IR sources in a sauna.

Embodiments of a smart mobility aid device may have sensors to collect, monitor, analyze and represent data including but not limited to activity tracking, biometrics and safety and emergency features. The activity tracking include number of steps, miles, and activity speed, user pressure on a device, activity types and analysis. The user biometric data includes but is not limited to blood work, blood pressure, blood sugar, heart rate, oxygen level/rate, ECG, EMG, muscle strain, humidity, UV, body temperature. Additional features include an emergency button, fall detection, warnings, and user pattern analysis changes. The mobility aid device is connected to other smart electronic device and/or the Internet using but not limited to Bluetooth, Wi-Fi, and or/and SIM card. The device gives the user or/and caregiver live feedback about user health metrics and status using a data representation method.

A method for regulating gas flows into and out of a patient includes repetitively forcing respiratory gases out of the lungs. Respiratory gases are prevented from entering back into the lungs during a time between when respiratory gases are forced out of the lungs. Periodically, an oxygen-containing gas is supplied to the lungs.

A system includes a guidance device that provides feedback to a user to compress a patient's chest at a rate of between about 90 and 110 compressions per minute and at a depth of between about 4.5 centimeters to about 6 centimeters. The system includes a pressure regulation system having a pressure-responsive valve that is configured to be coupled to a patient's airway. The pressure-responsive valve is configured to remain closed during successive chest compressions in order to permit removal at least about 200 ml from the lungs in order to lower intracranial pressure to improve survival with favorable neurological function. The pressure-responsive valve is configured to remain closed until the negative pressure within the patient's airway reaches about 7 cm H.sub.2O, at which time the pressure-responsive valve is configured to open to provide respiratory gases to flow to the lungs through the pressure-responsive valve.

A method of processing a raw acceleration signal, measured by an accelerometer-based compression monitor, to produce an accurate and precise estimated actual depth of chest compressions. The raw acceleration signal is filtered during integration and then a moving average of past starting points estimates the actual current starting point. An estimated actual peak of the compression is then determined in a similar fashion. The estimated actual starting point is subtracted from the estimated actual peak to calculate the estimated actual depth of chest compressions. In addition, one or more reference sensors (such as an ECG noise sensor) may be used to help establish the starting points of compressions. The reference sensors may be used, either alone or in combination with other signal processing techniques, to enhance the accuracy and precision of the estimated actual depth of compressions.