A monitoring apparatus for a human body includes a node network with at least one motion sensor and at least one acoustic sensor. A processor is coupled to the node network, and receives motion information and acoustic information from the node network. The processor determines from the motion information and the acoustic information a source of acoustic emissions within the human body by analyzing the acoustic information in the time domain to identify an event envelope representing an acoustic event, determining a feature vector related to the event envelope, calculating a distance between the feature vector and each of a set of predetermined event silhouettes, and identifying one of the predetermined event silhouettes for which the distance is a minimum.

A device includes an EMG processing application operable with a processing module to receive an output signal from EMG testing, wherein the output signal represents electrical activity of at least one muscle. The EMG processing application is operable to process the output signal to detect at least one type of waveform of a plurality of types of waveforms from the output signal and display the detected at least one type of waveform.

A device includes an EMG processing application operable with a processing module to receive an output signal from EMG testing, wherein the output signal represents electrical activity of at least one muscle. The EMG processing application is operable to process the output signal to detect at least one type of waveform of a plurality of types of waveforms from the output signal and display the detected at least one type of waveform.

Multi-modal sensing relating to joint acoustic emission and joint bioimpedance. Custom-design analog electronics and electrodes provide high resolution sensing of bioimpedance, microphones and their front-end electronics for capturing sound signals from the joints, rate sensors for identifying joint motions (linear and rotational), and a processor unit for interpretation of the signals. These components are packed into a wearable form factor, which also encapsulates the hardware required to minimize the negative effects of motion artifacts on the signals.

A new non-invasive tool for cartilage assessment, exercise and sports management, and prevention of osteoarthritis is provided. In various embodiments, cartilage condition is assessed using audible signals from joints. Assessment test results are used to provide feedback regarding joint stress and friction that is related to physiological or pathological loads. Data obtained from audible signals are processed to provide an index that can be interpreted by a user or third parties. The index is useful as a baseline for exercise practices, training routines, wellness programs, or rehabilitation protocols.

A device includes an EMG processing application operable with a processing module to receive audio output from EMG testing, wherein the audio output represents electrical activity of at least one muscle. The EMG processing application is operable to process the audio output to detect at least one type of waveform of a plurality of types of waveforms from the audio output and display the detected at least one type of waveform.

An apparatus for detecting the presence of pathogens in cerebrospinal fluid (CSF) within the central nervous system (CNS) includes a digital computer, a speaker unit and a microphone unit. The digital computer is programmed with generally available software which is capable of generating a spectrum of sound and receiving microphone data. The software is able to receive microphone signals and represent resulting data in graphical form showing sound intensity in dB as a function of frequency in kHz. An operator places the speaker and the microphone on the subject's body so that sound travels through at least a portion of the CNS, runs the software, and collects the resulting sound propagation data. If the propagation of sound through the CNS is indicative of altered CSF or CNS, then a disease state is suspected.

Disclosed herein are techniques for joint performance monitoring and diagnosis. A joint monitoring system includes a plurality of event detection sensors configured to be mounted on a wearer of the joint monitoring system, and a plurality of position tracking sensors configured to be mounted on the wearer. The plurality of event detection sensors is configured to generate detection signals for detecting an event in a joint region. The joint region includes a region within a body of the wearer and within a threshold distance of a joint. The detection signals from the plurality of event detection sensors includes information for determining a location of the event. The plurality of position tracking sensors is configured to record position information of one or more body parts associated with the joint in response to the detected event.

A system and method for monitoring heart function based on heart sounds (HS) is provided. The system includes electrodes configured to sense electrical cardiac activity (CA) signals over a period of time. An HS sensor is configured to sense HS signals over the period of time. The system includes memory to store specific executable instructions and includes one or more processors that, when executing the specific executable instructions, is configured to: identify a characteristic of interest (COI) of a heartbeat from the CA signals. The processors overlay a HS search window onto an HS segment of the HS signals based on the COI from the CA signals and calculate a center of mass (COM) for at least one of S1 or S2 HS based on the HS segment of the HS signals within the search window to obtain a corresponding at least one of S1 COM or S2 COM. The processors calculate at least one of an electromechanical activation time (EMAT) or a systolic interval (SI) based on the at least one of S1 COM or S2 COM and record the at least one of the EMAT or SI.

A method and device for detecting phrenic nerve stimulation (PNS) in, or using, a cardiac medical device. A test signal sensitive to contraction of a diaphragm of a patient may be sensed and signal artifacts of the test signal within each of a first window of the test signal prior to a predetermined cardiac signal and a second window of the test signal subsequent to the predetermined cardiac signal may be determined. The PNS beat criteria may be evaluated, for example, using the test signal, which may be a heart sounds signal.