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NeuroRPM is intended to quantify movement disorder symptoms during wake periods in adult patients 46 to 85 years of age with Parkinson's disease. These symptoms include tremor, bradykinesia, and dyskinesia. NeuroRPM is intended for clinic and home environments.

NeuroRPM is a software application for the Apple Watch that is prescribed by a health professional to quantify motor symptoms of Parkinson's disease including bradykinesia, dyskinesia, and tremor. NeuroRPM collects accelerometer and gyroscope data from the Apple Watch. The motion data are transmitted to cloud servers and analyzed using machine learning models developed to generate binary symptom classifications. Binary symptom classification output is generated every 15-minutes.

The Parky App is intended to quantify kinematics of movement disorder symptoms including tremor and dyskinesia, in adults (45 years of age or older) with mild to moderate Parkinson's disease.

Parky App is a symptom tracker mobile app for Parkinson's Disease patients. It collects motion data through Apple Watch continuously and quantifies tremor and dyskinesia episodes based on clinically validated MM4PD algorithm. Tracked symptoms are reported as daily, weekly and monthly. Each report is shared with the prescribing healthcare professional through email. The mobile app has a medication reminder module which the patients can manually enter their medication schedule, receive on-time reminder notifications on Apple Watch and iPhone and can respond to them as "taken" or "not yet taken". Parky also reports daily step counts provided by Apple Services - HealthKit.

The Rune Labs Kinematic System is intended to quantify kinematics of movement disorder symptoms including tremor and dyskinesia, in adults (45 years of age or older) with mild to moderate Parkinson's disease.

The Rune Labs Kinematic System collects derived tremor and dyskinesia probability scores using processes running on the Apple Watch, and then processes and uploads this data to Rune's cloud platform where it is available for display for clinicians. The Rune Labs Kinematic System uses software that runs on the Apple Watch to measure patient wrist movements. These movements are used to determine how likely dyskinesias or tremors are to have occurred. The times with symptoms are then sent to the Rune Labs Cloud Platform using the Apple Watch's internet connection, which is then displayed for clinician use. The Apple Watch contains accelerometers and gyroscopes which provide measurements of wrist movement. The Motor Fluctuations Monitor for Parkinson's Disease (MM4PD) is a toolkit developed by Apple for the Apple Watch that assesses the likely presence of tremor and dyskinesia as a function of time. Specifically, every minute, the Apple Watch calculates what percentage of the time that tremor and dyskinesia were likely to occur. The movement disorder data that is output from the Apple's MM4PD toolkit have been validated in a clinical study (Powers et al., 20211). The Rune Labs Kinematic System is software that receives, stores, and transfers the Apple Watch MM4PD classification data to the Rune Labs Cloud Platform where it is available for visualization by clinicians. The device consists of custom software that runs on the users' smart watch and web browsers.

The Personal Kinetigraph (PKG) is intended to quantify kinematics of movement disorder symptoms in conditions such as Parkinson's disease, including tremor, bradykinesia, and dyskinesia. It includes a medication reminder, an event marker and is intended to monitor activity associated with movement during sleep. The device is indicated for use in individuals 46 to 83 years of age.

The Personal Kinetigraph (PKG) Gen 2 Plus utilizes a PKG Watch (movement data logger) worn by the patient on their wrist over 6-to-10 day recording cycles. The PKG Watch continuously records and quantifies the kinematics of movement disorder symptoms such as bradykinesia (BK), dyskinesia (DK), tremor, immobility, and dyskinesia fluctuations, in movement disorder conditions such as Parkinson's disease. Proprietary PKG Analysis Algorithms are used to analyze the movement data and generate a PKG-2A Report, which provides the clinical provider with a summary of these movement disorder symptoms, plotted over the full recording period. The PKG-2A Report includes an additional feature that allows the plots to be annotated by a qualified PKG Reporter. The PKG Watch includes a medication reminder to notify the patient when it is time to take their medication, and an event marker for the patient to record when they have taken their prescribed medication. The Personal Kinetigraph (PKG) Gen 2 Plus System includes the GKCM Cloud Platform (PKG Clinic Server), a cloud-based service for receiving and processing the movement data files and generating PKG-2A Reports. The Personal Kinetigraph (PKG) Gen 2 Plus is a modified version of the predicate Personal Kinetigraph (PKG) System Model GKC-2000 (Gen 2) cleared under K161717, incorporating several new or enhanced features, including a Docking Station for charging the PKG Watch and uploading movement data files to the GKCM Cloud Platform, and a Clinic Portal (housed in the GKCM Cloud Platform), providing customer facing functions such as creating and editing patient details, scheduling medication reminders, raising PKG orders and viewing the PKG-2A Report. The Personal Kinetigraph (PKG) Gen 2 Plus also includes a PKG Tablet and PKG Dock Cable, cleared previously under K161717. The PKG Tablet is an off-the-shelf Android based tablet that runs a custom software application to configure the PKG Watch before a recording session, extract recorded data after a recording session, and upload this data to the GKCM Cloud Platform. The PKG Dock Cable connects the PKG Watch to the PKG Tablet for configuration before a recording session, and allows for uploading of the movement data to the PKG Clinic Server after the recording session. The PKG Tablet and PKG Dock Cable are not required when using the Docking Station and Clinic Portal. The Personal Kinetigraph (PKG) Gen 2 Plus system consists of the following key components: PKG Watch (movement data logger) including wrist bands; PKG Docking Station; PKG Clinic Portal; GKCM Cloud Platform (PKG Clinic Server); PKG Analysis Algorithms; PKG-2A Report; PKG Tablet; PKG Dock Cable; and 5-Bay charger.

The Personal Kinetigraph (PKG) is intended to quantify kinematics of movement disorder symptoms in conditions such as Parkinson's disease, including tremor, bradykinesia and dyskinesia. It includes a medication reminder, an event marker and is intended to monitor activity associated with movement during sleep. The device is indicated for use in individuals 46 to 83 years of age.

The new Personal Kinetigraph (PKG) System, Model GKC-2000 (Gen 2), utilizes a small, wrist-worn data logging activity monitor (the PKG Watch) that continuously records and quantifies the kinematics of movement disorder symptoms over a 6 to 10 day period in movement disorder conditions such as Parkinson's disease. At the end of the recording period, the movement recording data is uploaded via a Tablet application at the supervising clinic, to a cloud-based server. A report is produced using the recorded data that objectively distinguishes the movement patterns consistent with tremor, bradykinesia, dyskinesia and immobility. This information can be used by the clinician to assess the extent and severity of movement disorder symptoms, and how they vary throughout the day, and from day to day. The PKG Watch has a medication reminder to the patient that it is time to take their medication, and an event marker for the patient to record when they have taken their prescribed medication.

The Personal Kinetigraph (PKG) System is intended to quantify kinematics of movement disorder symptoms in conditions such as Parkinson's disease, including tremor, bradykinesia. It includes a medication reminder, an event marker and is intended to monitor associated with movement during sleep. The device is indicated for use in individuals 46 to 83 years of age.

The Personal Kinetigraph (PKG) System is a small, wrist-worn activity monitor that continuously records and quantifies the kinematics of movement disorder symptoms over a 6 to 10 day period in movement disorder conditions such as Parkinson's disease. A report is produced using the recorded data that objectively distinguishes the movement patterns consistent with tremor, bradykinesia, and immobility. This information can be used by the clinician to assess the extent and severity of movement disorder symptoms, and how they very throughout the day, and from day to day. The PKG Data Logger has a medication reminder to indicate to the patient that it is time to take their medication, and an event marker for the patient to record when they have taken their prescribed medication.

Kinesia is intended to monitor physical motion and muscle activity to quantify kinematics of movement disorder symptoms such as tremor and assess activity in any instance where quantifiable analysis of motion and muscle activity is desired.

Kinesia™ is designed to monitor and record motion and electrical activity of muscle to quantify kinematics of movement disorders such as tremor for research and diagnostic purposes. The patient unit consists of a wrist module and ring sensor. Motion sensors including accelerometers and gyroscopes are integrated into a finger worn unit to capture three dimensional motions. The finger worn sensor unit is worn on a finger band and is connected to a wrist worn module by a thin flexible wire. The wrist module provides an input for two channels of electromyography, battery power, on board memory, and an embedded radio for real-time wireless transmission of the collected signals. The wrist module is worn on a comfortable, adjustable wristband. The signals are communicated between the patient module and the computer unit using wireless technology based on 2.4-2.484 GHZ frequencies. Kinesia will consist of four major components: 1. Patient Module(consists of ring and wrist module) 2. Computer Unit 3. Electromyography Leads 4. Interface Software 1. The Patient Module includes a user worn ring and wrist module connected by a thin cable. The patient module monitors eight channels of data including three channels of accelerometers (linear acceleration sensors), three channels of gyroscopes (angular velocity sensors), and two channels of electrical muscle activity (EMG). The data can be transmitted in real-time over a wireless telemetry link to a computer or be stored in onboard memory. The wireless link can either transmit only (one-way) or transmit and receive (two-way). The basic functional feature of the component is to acquire signals from the subject, perform analog-to-digital conversion (when appropriate), encode, format, and transmit the signals to the Computer Unit or store data in on board memory. The Patient Module will operate on DC power from either rechargeable or replaceable batteries. The Patient Module includes a push button patient diary so the patient can indicate when they have taken their medication and when their symptoms are severe. 2. The Computer Unit will have the ability to only receive (one-way) or receive and transmit (two-way) data from the Patient Module. The basic functional feature of this component is to receive data packets from the patient unit, perform error detection and correction, and then send the data to the PC Operator interface where the data can be monitored in real time or stored and analyzed at a later time. 3: The Electromyography Leads provide an input for two channels of EMG recordings. The leads provide five standard snap connector inputs including two differential channels of EMG and a patient ground. The leads are connected to a lemo connector. The lemo connector attaches to the lemo input on the Patient Unit wrist module. 4. The Interface Software program consists of several software modules that allow the user to acquire, store, and review data as acquired by the hardware.