(241 days)
Not Found
Yes
The device description mentions the use of the "MM4PD algorithm" to quantify tremor and dyskinesia episodes based on motion data. While the summary doesn't explicitly state "AI" or "ML" in the dedicated section, the description of the algorithm's development and testing using large datasets of sensor data from Parkinson's patients and controls, including in-clinic and all-day data, strongly suggests the use of machine learning techniques for pattern recognition and quantification of movement disorders. The performance studies also describe validation against clinical evaluations and expert ratings, which is typical for ML-based algorithms in this domain.
No.
The device quantifies symptoms and provides reports and reminders, but it does not directly treat or diagnose a disease state.
Yes
The device quantifies kinematics of movement disorder symptoms (tremor and dyskinesia) using a clinically validated algorithm, and its outputs are reported to the prescribing healthcare professional, indicating its use in assessing a patient's condition.
No
The device description explicitly states it collects motion data through an Apple Watch, which is a hardware component. While the core functionality is software-based (the app and algorithm), it relies on and integrates with specific hardware for data acquisition.
Based on the provided information, the Parky App is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVD Definition: In Vitro Diagnostics are devices intended for use in the collection, preparation, and examination of specimens taken from the human body (such as blood, urine, or tissue) to provide information for the diagnosis, treatment, or prevention of disease.
- Parky App's Function: The Parky App collects motion data from an Apple Watch worn on the wrist. It analyzes this motion data to quantify kinematics related to movement disorder symptoms (tremor and dyskinesia). It does not analyze any specimens taken from the human body.
- Intended Use: The intended use is to quantify kinematics of movement disorder symptoms, not to perform tests on biological samples.
- Device Description: The description focuses on motion data collection and analysis, not on handling or analyzing biological specimens.
Therefore, the Parky App falls outside the scope of an In Vitro Diagnostic device. It is a software device that analyzes physiological data (motion) collected non-invasively.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device.
Intended Use / Indications for Use
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.
Product codes
GYD, NXQ, ISD
Device Description
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.
Mentions image processing
Not Found
Mentions AI, DNN, or ML
Not Found
Input Imaging Modality
Not Found
Anatomical Site
Not Found
Indicated Patient Age Range
adults (45 years of age or older)
Intended User / Care Setting
prescribing healthcare professional, in-clinic, out-of-clinic
Description of the training set, sample size, data source, and annotation protocol
An overview of the study design is provided in Fig. S1, which lists the design and validation phases with their respective number of subjects from each group. The document mentions "MM4PD development of tremor and dyskinesia algorithms used sensor data from both in-clinic tasks and all-day data in Parkinson's patients as well as several elderly, control subjects with no reported Parkinson's disease."
Description of the test set, sample size, data source, and annotation protocol
The algorithm was tested with a hold-out dataset that had all-day data and a single in-clinic visit from a subset of subjects in the longitudinal patient study. MM4PD outputs were further validated in 3 ways: i) a human factors pilot to ensure patients understood the smartwatch symptom profiles, ii) a comprehensive review to determine where smartwatch symptom profiles matched clinician expectations when used alongside a comprehensive patient history, and iii) a blinded matching task by 3 expert raters who classified smartwatch symptom profiles as pre or post-treatment for a given medication change.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
A clinical study with 343 participants with PD, including a longitudinal study of up to 6 months in a 225-subject cohort was conducted to demonstrate the ability of the MM4PD API used in Parky App to continuously track and categorize two common symptoms of Parkinson's disease: Tremor and Dyskinesia. M4PD measurements correlated to clinical evaluations of tremor severity (Rank Correlation Coefficient=0.80) and mapped to expert ratings of dyskinesia presence (P
§ 882.1950 Tremor transducer.
(a)
Identification. A tremor transducer is a device used to measure the degree of tremor caused by certain diseases.(b)
Classification. Class II (performance standards).
0
November 17, 2022
Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the FDA logo is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
H2O Therapeutics % Yagmur Selin Gulmus-Kolay CEO, H2O Therapeutics Mustafa Kemal Mah. 2119. Sok. No 3 Bilkent Cankava. Ankara 06510 Turkey
Re: K220820
Trade/Device Name: Parky App Regulation Number: 21 CFR 882.1950 Regulation Name: Tremor Transducer Regulatory Class: Class II Product Code: GYD, NXQ, ISD Dated: October 13, 2022 Received: October 18, 2022
Dear Yagmur Gulmus-Kolay:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part
1
801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4. Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Patrick Antkowiak -S
for Jay Gupta Assistant Director DHT5A: Division of Neurosurgical, Neurointerventional and Neurodiagnostic Devices OHT5: Office of Neurological and Physical Medicine Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
2
Indications for Use
510(k) Number (if known) K220820
Device Name Parky App
Indications for Use (Describe)
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.
Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
| Over-The-Counter Use (21 CFR 801 Subpart C)
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3
510(k) Summary
1. Submitter:
H2O Therapeutics Address: Mustafa Kemal Mah. 2119. Sok. No 3 Bilkent, Çankaya, Ankara, 06510 Turkey Contact Person: Ms. Yagmur Selin Gulmus Kolay Phone: +90 312 219 62 19 Email: selin@h2otherapeutics.com Date Prepared: November 15th, 2022
2. Device:
Trade Name: Parky App Common Name: Movement Disorder Monitoring System Classification Name: Tremor Transducer (21 CFR 882.1950) Device Classification: II Product Code(s): GYD, NXQ, ISD
3. Predicate Device
K213519, Rune Labs Kinematics System. The predicate device has not been recalled.
4. Device Description
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. Figure 1 provides a schematic demonstration of the system components and device operation.
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Image /page/4/Picture/0 description: The image shows the logo for h2o therapeutics. The logo is in black and white. The "h2o" is in a bold, sans-serif font, with a small degree symbol above the "o". Below "h2o" is the word "therapeutics" in a smaller, sans-serif font.
Image /page/4/Figure/1 description: This image shows a diagram of a patient using an Apple Watch and iPhone to track symptoms and share them with clinicians. The process starts with the patient downloading an app from the iOS App Store (step 1). The Apple Watch then collects sensor data and quantifies it as symptom information (step 2). The symptom information is periodically pulled from the Apple Watch by the Parky iOS application (step 3), and then sent to the cloud where reports are generated (step 4). Finally, the reports are shared with healthcare professionals (step 5), and the clinicians' decision-making process is supported by the provided reports (step 6).
Fig.1 System Components and Operation Overview
5. Indications for Use
The Parky App is intended to guantify kinematics of movement disorder symptoms including tremor and dyskinesia, in adults (45 years of age or older) with mild to moderate Parkinson's disease.
6. Comparison of Technological Characteristics to The Predicate
The proposed device, Parky App has identical working principle to the predicate, K213519, Rune Labs Kinematics System. Both devices collect movement recordings by the help of Apple Watch motion sensor and quantified Parkinson's Related movement disorders, specifically tremor and dyskinesia. Table 1 below provides a technological comparison of the proposed and predicate devices:
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Image /page/5/Picture/0 description: The image shows the logo for H2O therapeutics. The logo is in black and white. The "h2o" is in a bold, sans-serif font, and the "therapeutics" is in a smaller, lighter font.
| Characteristic | Proposed Device | Predicate, K213519 | Comparison |
|---|---|---|---|
| Intended Use | To measure the degree of tremor caused by certain diseases. | To measure the degree of tremor caused by certain diseases. | Identical to the predicate device. |
| Indications for Use | 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. | 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. | Identical to the predicate device. |
| Rx vs OTC | Rx | Rx | Identical to the predicate device. |
| Measurement Method | Recording of symptoms via wrist worn watch. | Recording of symptoms via wrist worn watch. | Identical to the predicate device. |
| Biocompatibility | Apple watch is manufactured from non-skin irritating and non-sensitizing materials. | Apple watch is manufactured from non-skin irritating and non-sensitizing materials. | Identical to the predicate device. |
| Electrical Safety | Electrical safety was assessed according to IEC 62368-1 (2014), "Audio/video, information and communication technology equipment - Part 1: Safety requirements." | Electrical safety was assessed according to IEC 62368-1 (2014), "Audio/video, information and communication technology equipment - Part 1: Safety requirements." | Identical to the predicate device. |
| Electromagnetic Compatibility (EMC) | The Apple Watch conforms to EU standards EN 301 | The Apple Watch conforms to EU standards EN 301 | Identical to the predicate device. |
| Characteristic | Proposed Device | Predicate, K213519 | Comparison |
| 489-1 (V2.2.20), EN | |||
| 301 489-3 (V2.1.1), EN | |||
| 301 489-17 (V3.2.0), | |||
| and EN 301 489-52 | |||
| (V1.1.0). | 489-1 (V2.2.20), EN | ||
| 301 489-3 (V2.1.1), | |||
| EN 301 489-17 | |||
| (V3.2.0), and EN 301 | |||
| 489-52 (V1.1.0). | |||
| Software | Software Validation | ||
| was conducted per | |||
| FDA Guidance | |||
| "Content of Premarket | |||
| Submissions for Device | |||
| Software Functions" | |||
| issued on May 11, | |||
| 2005 | Software testing | ||
| established that the | |||
| system meets the | |||
| software requirements | |||
| and user needs for the | |||
| intended uses. | Identical to the | ||
| predicate device. | |||
| Cybersecurity | Cybersecurity threat | ||
| analysis and mitigation | |||
| has been conducted | |||
| according to | |||
| "Content of Premarket | |||
| Submissions for | |||
| Management of | |||
| Cybersecurity in | |||
| Medical Devices". | Not specified. | We have | |
| conducted | |||
| extensive | |||
| cybersecurity | |||
| testing and | |||
| mitigation efforts | |||
| to ensure the | |||
| security of our | |||
| patient data. | |||
| Outputs and | |||
| Features | The Rune Lab device | ||
| outputs are the | |||
| percentage of the time | |||
| that tremor and | |||
| dyskinesia were | |||
| likely to occur. | The Rune Lab device | ||
| outputs are the | |||
| percentage of the time | |||
| that tremor and | |||
| dyskinesia were | |||
| likely to occur. | Identical to the | ||
| predicate device. | |||
| Data Transmission | Cellular or Wireless | ||
| Network | Cellular and Wireless | ||
| Network | Identical to the | ||
| predicate device. | |||
| Over-the-Counter | |||
| Software | Utilizes Apple's | ||
| MM4PD API and Apple | |||
| Watch's accelerometer | |||
| to measure and | |||
| quantify dyskinesia and | |||
| tremor related to | |||
| Parkinson's Disease | Utilizes Apple's | ||
| MM4PD API and | |||
| Apple Watch's | |||
| accelerometer to | |||
| measure and quantify | |||
| dyskinesia and tremor | Identical to the | ||
| predicate device. | |||
| Characteristic | Proposed Device | Predicate, K213519 related to Parkinson's Disease | Comparison |
| Performance Data | Device Measurements | ||
| highly correlated to | |||
| clinical evaluations of | |||
| tremor severity (Rank | |||
| Correlation | |||
| Coefficient=0.80) and | |||
| mapped to expert | |||
| ratings of dyskinesia | |||
| presence (P1 Powers R, Etezadi-Amoli M, Arnold EM, Kianian S, Mance I, Gibiansky M, Trietsch D, Alvarado AS, Kretlow JD, Herrington TM, Brillman S, Huang N, Lin PT, Pham HA, Ullal AV. Smartwatch inertial sensors continuously monitor real-world motor fluctuations in Parkinson's disease. Sci Transl Med. 2021 Feb 3;13(579):eabd7865. doi: 10.1126/scitranslmed.abd7865. PMID: 33536284. |
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Image /page/8/Picture/0 description: The image shows the logo for "h2o therapeutics". The logo is in black and white. The "h2o" is in a bold, sans-serif font, and the "therapeutics" is in a smaller, lighter font.
- Electrical safety was assessed according to IEC 62368-1 (2014), "Audio/video, information and communication technology equipment – Part 1: Safety requirements."
- Apple Watch conforms to EU standards EN 301 489-1 (V2.2.20). EN 301 489-3 (V2.1.1). -EN 301 489-17 (V3.2.0), and EN 301 489-52 (V1.1.0).
7.2. Biocompatibility and Sterility
Parky App uses the same generation of Apple Watch as the predicate device. All patient contacting materials are identical to the predicate device. The proposed device is not intended to be used as sterile.
8. Software
8.1. Software Validation and Verification
Software documentation was provided according to the FDA guidance titled: "Content of Premarket Submissions for Device Software Functions", issued on May 11, 2005. The level of concern was moderate as defined in the guidance.
8.2. Cybersecurity
Parky is an internet-connected app. Thus, a Cybersecurity Threat Assessment and Remediation Analysis (CTARA) was conducted, and all risks were mitigated per the FDA guidance titled: "Content of Premarket Submissions for Management of Cybersecurity in Medical Devices" issued on October 18, 2018.
9. Performance Data
9.1. Clinical Testing
A clinical study' with 343 participants with PD, including a longitudinal study of up to 6 months in a 225-subject cohort was conducted to demonstrate the ability of the MM4PD API used in Parky App to continuously track and categorize two common symptoms of Parkinson's disease: Tremor and Dyskinesia. M4PD measurements correlated to clinical evaluations of tremor severity (Rank Correlation Coefficient=0.80) and mapped to expert ratings of dyskinesia presence (P2 Powers R, Etezadi-Amoli M, Arnold EM, Kianian S, Mance I, Gibiansky M, Trietsch D, Alvarado AS, Kretlow JD, Herrington TM, Brillman S, Huang N, Lin PT, Pham HA, Ullal AV. Smartwatch inertial sensors continuously monitor real-world motor fluctuations in Parkinson's disease. Sci Transl Med. 2021 Feb 3:13(579):eabd7865. doi: 10.1126/scitranslmed.abd7865. PMID: 33536284.
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Image /page/9/Picture/0 description: The image shows the logo for H2O Therapeutics. The logo is composed of the letters "h2o" in bold, black font, with a small degree symbol above the "o". Below the "h2o" is the word "therapeutics" in a smaller, lighter gray font. The logo is simple and modern, and the use of the chemical formula for water suggests a focus on hydration or water-based therapies.
the clinician's expectations in 94% for cases of full patient history and 87,5% for cases of blind classification with 3 expert raters. There were no serious adverse events associated with the use of the device.
Table S1 below summarizes the patient demographics across all studies reported by Powers et al., 2021.
| | Pilot study
PD patients in-clinic + 1 week live-on | Longitudinal patient study
PD patients long-term live-on | Longitudinal control study
Elderly controls |
|----------------------------------------------|-------------------------------------------------------|-------------------------------------------------------------|------------------------------------------------|
| Age [± Standard Dev] | 68.1 yrs [±9.0] | 71.4 yrs [±8.9] | 74.7 yrs [±5.4] |
| Years with PD [± Standard Dev] | 6.5 yrs [±5.6] | 10.3 yrs [±6.5] | n/a |
| Gender | 36 Female, 82 Male | 69 Female, 156 Male | 85 Female, 85 Male, 1 unknown |
| Most Affected Side | 62 Right / 39 Left / 17 unspecified | 105 Right / 120 Left | n/a |
| History of Tremor | - | 166/225 Participants | n/a |
| History of Dyskinesia
(History of Chorea) | - | 94/225 Participants
(66/94 with dyskinesia) | n/a |
| History of Freezing Gait | - | 85/225 Participants | n/a |
| History of Slow Gait | - | 172/225 Participants | n/a |
| | | *self-reported history | |
Table S1. Study demographics. Patient demographics across all studies
An overview of the study design is provided below in Figure S1. This figure lists the design and validation phases with their respective number of subjects from each group.
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Image /page/10/Figure/1 description: The image shows the MM4PD development and validation process for tremor and dyskinesia algorithms. The development process includes three stages: design in-clinic tasks, design all-day data, and test with hold-out data. The validation process includes human factors testing with 36 patient surveys, clinical decision support with 112 profiles evaluated by a single clinician, and a blinded matching task with 10 cases evaluated by 3 clinicians. The image also shows the number of patients and controls used in each stage of the development process.
Fig. S1. Overview of data collected for MM4PD development and validation. MM4PD
development of tremor and dyskinesia algorithms used sensor data from both in-clinic tasks and all-day data in Parkinson's patients as well as several elderly, control subjects with no reported Parkinson's disease. Some patients provided in-clinic data with both tremor across different sessions. The algorithm was tested with a hold-out dataset that had all-day data and a single in-clinic visit from a subset of subjects in the longitudinal patient study. MM4PD outputs were further validated in 3 ways: i) a human factors pilot to ensure patients understood the smartwatch symptom profiles, ii) a comprehensive review to determine where smartwatch symptom profiles matched clinician expectations when used alongside a comprehensive patient history, and iii) a blinded matching task by 3 expert raters who classified smartwatch symptom profiles as pre or post-treatment for a given medication change.
As described in Fig S1. above and detailed in Table 1 below, to design and validate MM4PD, 9 study results are presented within the Clinical Trial Report (Powers et al., 2021):
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Image /page/11/Picture/0 description: The image shows the logo for h2o therapeutics. The logo is in black and consists of the letters "h2o" with a degree symbol above the "o". Below the "h2o" is the word "therapeutics" in a smaller font. The logo is simple and modern.
| 1a | Tremor algorithm design with in-clinic tasks | 1b | Dyskinesia algorithm design with in-clinic tasks |
|---|---|---|---|
| 2a | Tremor algorithm design with all-day data | 2b | Dyskinesia algorithm design with all-day data |
| Design lock for MM4PD Tremor and Dyskinesia Algorithms: minute-by-minute measurements ready to be tested in | |||
| real-world continuous use to match MDS-UPDRS tremor constancy | |||
| 3a | Tremor algorithm test with hold-out data during the | ||
| longitudinal patient study | 3b | Dyskinesia algorithm test with hold-out data | |
| during the longitudinal patient study | |||
| Patient symptom profiles generated based on 15 min averages of MM4PD minute-by-minute outputs | |||
| 4 | Human factors testing for symptom profiles through | ||
| patient surveys | |||
| 5 | Evaluation of symptom profiles by a clinician with access | ||
| to patient history | |||
| 6 | Evaluation of symptom profiles by 3 blind clinicians | ||
| without access to patient history |
Table 1. Description of Design and Validation Studies Out of all 9 study results listed above, 3a and 3b were used to validate the tremor and dyskinesia algorithm performance in hold-out data sets and out-of-clinic settings, respectively. (Please see Fig 3E and 4E). 5 and 6 validate that the patient symptom profiles (generated through 15 minutes averages of MM4PD minute-by-minute outputs for tremor and dyskinesia separately) match clinician expectations based on MDS-UPDRS constants either with or without access to patient history, respectively (Please see Fig 6)
Image /page/11/Figure/3 description: This image is a boxplot showing the relationship between MDS-UPDRS tremor constancy and mean daily tremor percentage. The x-axis represents MDS-UPDRS tremor constancy, ranging from 0 to 4, while the y-axis represents the mean daily tremor percentage, ranging from 0 to 35. The sample size for each tremor constancy level is indicated above each boxplot, with n=19 for 0, n=6 for 1, n=4 for 2, and n=7 for both 3 and 4. The correlation coefficient (ρ) between the two variables is 0.72, indicating a strong positive correlation.
Fig. 3E. Smartwatch estimates of tremor severity and presence correlate to MDS-UPDRS ratings Mean daily smartwatch tremor estimates correlated with MDS-UPDRS tremor constancy ratings from the subject's last in-clinic visit in hold-out (n = 43) set with a Spearman's rank correlation of 0.72.
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Image /page/12/Picture/0 description: The image shows the logo for H2O Therapeutics. The logo is black and white. The "h2o" is in lowercase letters, and the "o" has a degree symbol above it. The word "therapeutics" is written in a smaller font below the "h2o".
Image /page/12/Figure/1 description: The image is a boxplot comparing the percentage of time dyskinesia is detected in two groups: "No DK" and "Chorea". The y-axis represents the percentage of time dyskinesia is detected. The "No DK" group has a sample size of n=47, while the "Chorea" group has a sample size of n=10. A horizontal line with an asterisk above the two boxplots indicates a statistically significant difference between the two groups.
Fig. 4E. Smartwatch choreiform dyskinesia detection matches clinical evaluation. In a hold-out dataset (n=57) from the longitudinal patient study, the percentage of time dyskinesias were detected for the chorea group (5.9 ± 5.3%) significantly differed from subjects with no reported dyskinesias (2.0 ± 2.2%) (P = 0.027, Wilcoxon rank sum test)
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Image /page/13/Picture/0 description: The image contains the logo for "h2o therapeutics". The "h2o" is in bold, dark gray font, with a degree symbol above the "o". Below "h2o" is the word "therapeutics" in a smaller, lighter gray font. The logo is simple and modern.
Image /page/13/Figure/1 description: The image shows two sets of data, each with a pie chart and a corresponding table. The first set, labeled 'A', presents a clinician evaluation with a pie chart showing 94% matched clinician's expectation and 6% unexpected but plausible, based on 104 patients. The table below details a longitudinal patient study with 112 patients undergoing medication or DBS changes, resulting in 98 symptom data changes matching medication change and 6 unexpected but plausible.
Fig. 6. Smartwatch symptom profiles match clinician expectations and provide
quantitative evidence for cases with uncertainty. The clinician reviewed the smartwatch symptom profiles of 112 subjects in the longitudinal patient study who underwent treatment changes. (A) Symptom changes matched the clinician's expectation of the prescribed medication change in 94% of cases. Unexpected cases revealed plausible incidence of known side effects to medications. (B) Three blinded movement disorder specialists classified 10 sets of profiles as pre-or post-treatment using only the patient's medication schedule and MDS-UPDRS tremor and dyskinesia ratings from the intake visit; 87.5% of classifications were correct; three misclassifications occurred because raters presumed that an alternate medication had a dominant effect. Six cases were deemed inconclusive and were excluded.
In summary, MM4PD algorithm outputs significantly correlate with MDS-UPDRS scores of the patients. In addition, system profiles generated through 15-minute means of MM4PD outputs match clinician expectations in out-of-clinic settings.