Systems, methods, and devices include a neurological function assessment system involving a first assessment tool (e.g., hammer) with one or more first sensors. The system includes a second assessment tool being a wearable device operable to wrap around a body part of a subject. One or more second sensors are disposed on the wearable device operable to sense a target area at the body part. The system collects first sensor data, from the first assessment tool, corresponding to an assessment event at the first assessment tool; and collects second sensor data, from the second assessment tool, corresponding to the assessment event. Additionally, the system presents, at a display, an indication of an objective neurological assessment parameter value calculated based on the first sensor data and the second sensor data. An objective neurological assessment parameter value can be calculated based on the first sensor data and/or the second sensor data.

Systems, methods, and devices include a frustrated total internal refraction (FTIR) based scanning device. The FTIR based scanning device has a transparent media and one or more electromagnetic wave emitters operable to provide a scanning light into the transparent media during a sample scanning procedure. One or more electromagnetic wave sensors, cameras, and/or microscopes are directed at a detection surface of the transparent media. These detection component(s) receive scattered light passing from the sample contact surface through the detection surface. The device uses the scattered light to represent a surface topology or a material composition of a sample contacting the sample contact surface during the sample scanning procedure. Additionally, the one or more electromagnetic wave emitters can include a plurality of LEDs or electromagnetic wave emitters corresponding to a plurality of different wavelengths which are used to generate an image of a 3D topology from the scattered light.

Systems, methods, and devices include one or more acoustics-controlling device(s). The acoustics-controlling device(s) comprise implants, fixations, patches, and/or coatings formed of a metamaterial to create a particular behavior when exposed to sound waves. An acoustic metamaterial manipulates the acoustic waves that reach it. The metamaterial has a non-uniform material distribution, a non-uniform geometry, and/or a non-uniform material property, such as a non-uniform density, a non-uniform modulus of elasticity, a non-uniform bulk modulus, combinations thereof, and so forth. The system(s) include acoustic controlling patches and implants which control a path of an acoustic signal generated by one or more speakers. An acoustic-controlling patch can include an acoustic Fresnel lens or an acoustic Luneburg lens formed onto a substrate. Furthermore, manipulating the acoustic signal includes focusing the acoustic signal, forming an acoustic vortex from the acoustic signal, steering the acoustic signal, guiding the acoustic signal, or bending the acoustic signal.

Systems, methods, and devices include a wearable device to stimulate or analyze biological systems or implantable objects. The system includes a substrate material and a plurality of acoustic actuators disposed on the substrate material. The plurality of acoustic actuators are operable to generate an acoustic stimulation signal directed to a target area. The system also includes a plurality of acoustic sensors disposed on the substrate material and operable to receive an acoustic response signal from the target area. Furthermore, a plurality of electrical electrodes disposed on the substrate material are operable to generate an electrical stimulation signal directed to the target area and receive an electrical response from the target area. The substrate material forms a sleeve or a cuff, a glove, a head cap, a back harness, a waist binder, a torso binder, and/or an abdominal binder.

An adhesive patch for monitoring acoustic signals from a human or animal body, comprising a skin contact surface, converting means for recording both body acoustic signals and environmental acoustic noise, reducing the body signals by the recorded noise, and providing a first electric output signal. The patch also comprising an adhesive element and a compression structure for attaching the converting means to the skin surface. The patch further comprises transmitting means for transmitting the output signal to a peripheral device.

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 method comprising to analyze the captured video data of the patient's body parts and to generate patient motion metrics, patient posture metrics, and patient gait metrics for each exercise routine completed by the patient based on the analyzed video data; store, in a database, the generated patient motion metrics, the patient posture metrics and the patient gait metrics for each of the completed exercise routines, wherein the generated patient motion metrics, the generated patient posture metrics and the generated patient gait metrics are used to track patient progress during physical therapy sessions, diagnose movement disorders, and provide personalized, data-driven treatment plans to enhance immediate outcomes and long-term recovery with respect to the musculoskeletal and neurological disorders; apply motion amplification algorithms to enhance the additional video data to provide clarity of tremor movements; apply edge detection to enhance tremor movement boundaries and detection; generate tremor amplitude measurements and tremor frequency measurements based on the motion amplification and edge detection algorithms; and store, in the database, the generated tremor amplitude measurements and tremor frequency measurements, wherein the generated tremor amplitude measurements and tremor frequency measurements are analyzed for diagnosis and monitoring of disorders such as Parkinson's disease and Essential Tremor.

A leadless implantable medical device (IMD) and method of using same are provided. The IMD comprises: a housing, a fixation element, electrodes configured to sense electrical cardiac activity (CA) signals over a period of time, an HS sensor configured to sense HS signals over the period of time, memory to store specific executable instructions, and one or more processors. The one or more processors and method: identify a characteristic of interest (COI) of a heartbeat from the CA signals, calculate a center of mass (COM) for at least one HS based on the HS signals to obtain a corresponding at least one HS COM, and calculate at least one of a therapy-related (TR) delay or a sensing-related (SR) blanking interval (BI) based on the at least one HS COM.

A method comprising to analyze the captured video data of the patient's body parts and to generate patient motion metrics, patient posture metrics, and patient gait metrics for each exercise routine completed by the patient based on the analyzed video data; store, in a database, the generated patient motion metrics, the patient posture metrics and the patient gait metrics for each of the completed exercise routines, wherein the generated patient motion metrics, the generated patient posture metrics and the generated patient gait metrics are used to track patient progress during physical therapy sessions, diagnose movement disorders, and provide personalized, data-driven treatment plans to enhance immediate outcomes and long-term recovery with respect to the musculoskeletal and neurological disorders; apply motion amplification algorithms to enhance the additional video data to provide clarity of tremor movements; apply edge detection to enhance tremor movement boundaries and detection; generate tremor amplitude measurements and tremor frequency measurements based on the motion amplification and edge detection algorithms; and store, in the database, the generated tremor amplitude measurements and tremor frequency measurements, wherein the generated tremor amplitude measurements and tremor frequency measurements are analyzed for diagnosis and monitoring of disorders such as Parkinson's disease and Essential Tremor.

A leadless implantable medical device (IMD) and method of using same are provided. The IMD comprises: a housing, a fixation element, electrodes configured to sense electrical cardiac activity (CA) signals over a period of time, an HS sensor configured to sense HS signals over the period of time, memory to store specific executable instructions, and one or more processors. The one or more processors and method: identify a characteristic of interest (COI) of a heartbeat from the CA signals, calculate a center of mass (COM) for at least one HS based on the HS signals to obtain a corresponding at least one HS COM, and calculate at least one of a therapy-related (TR) delay or a sensing-related (SR) blanking interval (BI) based on the at least one HS COM.