Clinical trial NCT03366558: Identification of Motor Symptoms Related to Parkinson's Disease Using Motion Tracking Sensors at Home
Official title: Sensor-based Motion Characterization in Patients With Parkinson's Disease
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Parkinson Disease
Keywords: motion detectors
early stage Parkinson's disease
advanced Parkinson's disease
UPDRS
observational study with non-diseased controls
Lead sponsor: Satakunta Central Hospital
Sponsor class: OTHER
Collaborators: name: Tampere University of Technology
First posted: 2017-12-08
Enrollment: 97
Sex: ALL
Minimum age (years): 30
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients having Parkinson's disease will be recruited with two methods: A) Unit of Neurology at Satakunta Central Hospital searches from the patient records potential participants, who have visited the hospital during the past 5 years with ICD-10 code G20. B) In case not enough participants are found from the Unit of Neurology, advertisements in local newspapers, in local Parkinson's disease patient association newsletters and in the web site of the hospital will be utilized.

For recruiting volunteers without Parkinson's disease into the reference group, an advertisement is placed in local newspapers and in the web pages of the hospital.

Brief summary: Parkinson's disease (PD) is a chronic and progressive neurological movement disorder, meaning that symptoms continue and worsen over time. Nearly 10 million people worldwide are living with Parkinson's disease. Finding cost-effective non-invasive monitoring techniques for detecting motor symptoms caused by Parkinson's disease are potentially of significant value for improving care. Of the PD symptoms, the motor symptoms are the most common and detectable signs that can be assessed unobtrusively for both diagnosis and for evaluating the effectiveness of the treatments.

The goal of our study is to find methods for identifying and classifying the motor symptoms caused by Parkinson's disease. Focus of the study is on long-term motion tracking measurements conducted at home during normal everyday life. Both accelerometers connected to arm and leg and mobile phone inbuilt sensors carried in the belt are utilized in the study. The research has two main objectives / hypotheses:

1. Can the motor symptoms related to different levels of Parkinson's disease be identified using motion tracking sensors? The first objective includes extracting and screening the motion differences of patients in early stages of the diseases in comparison with the patients in developed stages (patients having hypokinesia, dyskinesia and state changes) of the diseases and their differences with healthy control elderly adults using advanced signal and data analytics. Data from questionnaires and walking test conducted in the hospital environment are utilized as comparison points. Goal is to test the hypothesis that the amount of motor symptoms can be detected and the three groups can be reliably separated using sensor data.
2. Can the time when the Parkinson medicine is taken be detected from the movement signals?

A sample of 50 volunteer PD patients with early stage of the disease (no dyskinesia and state changes), plus 50 volunteer PD patients in the later stage of the disease (having dyskinesia and state changes), plus 50 volunteers who do not have Parkinson's disease will be recruited for the research.

Study starts with a telephone screening and visit to the hospital. Background characteristics and stage of the Parkinson's disease is evaluated in the hospital using a UPDRS questionnaires (Unified Parkinson's Disease Rating Scale; Finnish version) and a standardized 20-step walking test. Before the walking test, accelerometer sensors are attached to the shank and on the nondominant wrist. In addition, the participant wears a smart mobile phone with embedded accelerometer and gyroscope sensors. Based on the questionnaires and walking test study physiotherapist classifies the participant into one of the three study groups.

The major part of the study involves a 3-day motion screening in a free-living setting in which the subjects are wearing the abovementioned sensors for as long duration as they comfortably can and are willing. This 3-day study starts immediately after completion of the 20-step walking test in the hospital. During the 3-day study, subjects are free to live their lives without any additional tests. Subjects mark down the time when they take their Parkinson medication.


Eligibility criteria: Inclusion Criteria:

(A) participants must be 30 years of age or older. (B) (for the Parkinson groups) diagnosed with PD (ICD-10 code G20) by a physician (neurologist or physician specializing in neurology). (C) They should be able to walk at least 20 steps unassisted (subjects are allowed to get help from assistive devices but not from other persons).

Exclusion Criteria:

(A) The subjects must not be receiving any deep brain stimulation (DBS) treatment while they are participating, but intraduodenal administration of levodopa (Duodopa®) or intradermal administration of apomorphine (Apogo® or Dacepton®) is accepted. (B) .Other extrapyramidal syndromes such as MSA (multiple system atrophy), PSP (progressive supranuclear palsy), CBD (corticobasal degeneration), LBD (Lewy body dementia) or dopamine antagonist drug (such as antipsychotic drug, metoclopramide) induced Parkinsonism will be excluded.

Primary outcomes:
measure: Accuracy of the classification of data from movement sensors in relation to the detected motor symptoms
timeFrame: 3 days
measure: Accuracy of the detection of the time when the Parkinson medicine was taken
timeFrame: 3 days
Secondary outcomes:
Other outcomes:
Locations:
city: Pori
country: Finland
facility: Satakunta Central Hospital, Unit of Neurology
Study officials:
affiliation: Tampere University of Technology
name: Jari Ruokolainen, PhD
role: STUDY_CHAIR
affiliation: Tampere University of Technology
name: Hannu Nieminen, PhD
role: STUDY_DIRECTOR
affiliation: Satakunta Central Hospital
name: Juha Puustinen, MD, PhD
role: STUDY_DIRECTOR
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