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Ambulatory and Remote Monitoring of Parkinson’s Disease Motor Symptoms
Published in Daniel Tze Huei Lai, Rezaul Begg, Marimuthu Palaniswami, Healthcare Sensor Networks, 2016
Joseph P. Giuffrida, Edward J. Rapp
The translation of existing medical technologies to mainstream clinical use can significantly impact healthcare access, costs and outcomes, including telehealth technologies for remote diagnosis and mobile, portable diagnostics for home-based monitoring. Parkinson’s disease (PD) is a neurodegenerative movement disorder with no cure that currently affects 6.3 million people worldwide (Davis, Edin, and Allen 2010). However, unlike the cardiac market, in which Holter monitors are a clinically accepted standard for assessing arrhythmias, quantitative and automated systems for ambulatory assessment of Parkinson’s disease motor symptoms are currently not in widespread clinical use. This limits the opportunity for continuous remote monitoring of motor symptoms to capture complex fluctuation patterns and optimize treatment protocols, stifles utilization of sensitive motion-sensing technology to detect subtle motor changes for new pharmaceutical interventions and limits access to treatment optimization for socio-economically and geographically disparate patient populations not in close proximity to movement disorder specialists. The development of Kinesia™, a wireless system of biokinetic sensors for quantitative and more continuous assessment of motor symptoms, addresses this need for telehealth technologies in the Parkinson’s disease market. The patient-worn technology utilizes a sensor network consisting of microelectromechanical accelerometers and gyroscopes for motion sensing integrated with wireless transmission of the biokinetic data to a computer for analysis. The patient puts the system on the finger and wrist and then follows on-screen video instructions to complete upper-extremity motor tasks typically performed in the clinic. Software and algorithms automatically process the sensor data into reports to document symptom severity. Utilizing this technology, clinicians can capture clinically relevant parameters of movement disorders typically addressed during an office visit but can also do so in the patient’s home environment on a more continuous basis with a standardized and quantitative assessment platform.
Context-Driven Variability in Personality and Interpersonal Behavior: Evidence-Based Assessment Strategies
Published in Journal of Personality Assessment, 2022
Ambulatory Assessment (AA) encompasses a wide range of methods used to assess behavior in the natural environment. For example, in ecological momentary assessment studies participants provide in-the-moment reports of their interpersonal interactions using smartphone-based electronic diaries. Using this approach, Roche et al. (2016) assessed temporal and contextual variations in various indices of personality impairment and interpersonal functioning in vivo, documenting predictable variations over time and across context; Roche et al. further found that these changes were triggered by cognitive and affective dynamics (e.g., negative emotions, cognitive distortions) that would be expected to affect self- and interpersonal behavior. Similar results were obtained by Jahng et al. (2011), who used AA methods to identify events that are followed by increases in depression or anxiety. Digital technologies are not yet available in all assessment contexts, but as data continue to accumulate use of AA to quantify contextual variations in personality in vivo will increase (see Bettis et al., 2021).
Using REDCap for ambulatory assessment: Implementation in a clinical trial for smoking cessation to augment in-person data collection
Published in The American Journal of Drug and Alcohol Abuse, 2019
Rachel L. Tomko, Kevin M. Gray, Stephanie R. Oppenheimer, Amy E. Wahlquist, Erin A. McClure
Ambulatory assessment (1) refers to the collection of self-report, physiological, or other data from individuals in their natural environments during everyday life. Researchers have employed ambulatory assessment to study individuals’ behavior in real-time in naturalistic settings for over three decades. Several reviews have addressed advantages, challenges, and design considerations when implementing ambulatory assessment with clinical populations (2–5). We argue that ambulatory assessment may yield valuable information when used to track participant behavior within a randomized controlled clinical trial. ambulatory assessment may be used to determine whether and when real-world changes in physiology and/or behavior occur during the course of treatment. A number of researchers have already employed ambulatory assessment in clinical trials of substance use disorder treatments to examine real-world outcomes that could not otherwise be examined with traditional methodologies (6–9).
Ecological momentary assessment for rehabilitation of chronic illness and disability
Published in Disability and Rehabilitation, 2018
Ashlee McKeon, Michael McCue, Elizabeth Skidmore, Michelle Schein, Jamie Kulzer
With EMA (also known as ambulatory assessment or experience sampling; [12]), individuals are prompted, often through portable technology, such as a smartphone or wristwatch, and usually at multiple times points throughout the day to report on their current state relevant to outcomes of interest (e.g., mood or physical symptoms). This method of momentary data collection eliminates the need for the individual to recall past experiences, reducing concerns over inaccurate self-reporting by asking the individual only about their experience in that exact moment in time [13]. Data collection can be done through an active approach, where the individual is required to input data manually (e.g., entering data into a smartphone application), or through a more passive process, where data are collected without any conscious effort or input from the individual (e.g., wearable activity monitors).