The miniaturization, sophistication, proliferation, and accessibility of technologies are enabling the capturing of more and previously inaccessible phenomena in Parkinson disease (PD). However, more information has not translated into greater understanding of disease complexity to satisfy diagnostic and therapeutic needs. Challenges include non-compatible technology platforms, the need for wide-scale and long-term deployment of sensor technology (in particular among vulnerable elderly patients), and the gap between the “big data” acquired with sensitive measurement technologies and their limited clinical application. Major opportunities could be realized if new technologies are developed as part of open-source and/or open-hardware platforms enabling multi-channel data capture, sensitive to the broad range of motor and non-motor problems that characterize PD, and adaptable into self-adjusting, individualized treatment delivery systems. The International Parkinson and Movement Disorders Society Task Force on Technology is entrusted to convene engineers, clinicians, researchers, and patients to promote the development of integrated measurement and closed-loop therapeutic systems with high patient adherence that also serve to: 1) encourage the adoption of clinico-pathophysiologic phenotyping and early detection of critical disease milestones; 2) enhance tailoring of symptomatic therapy; 3) improve subgroup targeting of patients for future testing of disease modifying treatments; and 4) identify objective biomarkers to improve longitudinal tracking of impairments in clinical care and research. This article summarizes the work carried out by the Task Force toward identifying challenges and opportunities in the development of technologies with potential for improving the clinical management and quality of life of individuals with PD.

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, "wearable," sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that "learn" from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

We tested the feasibility of a computer based at-home testing device (AHTD) in early-stage, unmedicated Parkinson’s disease (PD) patients over 6 months. We measured compliance, technical reliability, and patient satisfaction to weekly assessments of tremor, small and large muscle bradykinesia, speech, reaction/movement times, and complex motor control. relative to the UPDRS motor score. The AHTD is a 6.5 x 10 computerized assessment battery. Data are stored on a USB memory stick and sent by internet to a central data repository as encrypted data packets. Although not designed or powered to measure change, the study collected data to observe patterns relative to UPDRS motor scores. Fifty-two PD patients enrolled, and 50 completed the six month trial, 48 remaining without medication. Patients complied with 90.6% of weekly 30-minute assessments, and 98.5% of data packets were successfully transmitted and decrypted. On a 100-point scale, patient satisfaction with the program at study end was 87.2 (range 80–100). UPDRS motor scores significantly worsened over 6 months, and trends for worsening over time occurred for alternating finger taps (p=.08), tremor (p=.06) and speech (p=.11). Change in tremor was a significant predictor of change in UPDRS (p=0.047) and was detected in the first month of the study. This new computer-based technology offers a feasible format for assessing PD-related impairment from home. The high patient compliance and satisfaction suggest the feasibility of its incorporation into larger clinical trials, especially when travel is difficult and early changes or frequent data collection are considered important to document.

During in vivo intracerebral infusions, the ability to perform accurate targeting towards a 3D-specific point allows control of the anatomical variable and identification of the effects of variations in other factors. Intraoperative MRI navigation systems are currently being used in the clinic, yet their use in nonhuman primates and MRI monitoring of intracerebral infusions has not been reported. In this study rhesus monkeys were placed in a MRI-compatible stereotaxic frame. T1 MRIs in the three planes were obtained in a 3.0T GE scanner to identify the target and plan the trajectory to ventral postcommisural putamen. A craniotomy was performed under sterile surgical conditions at the trajectory entry point. A modified MRI-compatible trajectory guide base (Medtronic Inc.) was secured above the cranial opening and the alignment stem applied. Scans were taken to define the position of the alignment stem. When the projection of the catheter in the three planes matched the desired trajectory to the target, the base was locked in position. A catheter replaced the alignment stem and was slowly introduced to the final target structure. Additional scans were performed to confirm trajectory and during the infusion of a solution of gadoteridol (ProHance, Bracco Diagnostics; 2 mM/L) and bromophenol blue (0.16 mg/ml) in saline. Monitoring of the pressure in the infusion lines was performed using pressure monitoring and infusion pump controller system (Engineering Resources Group Inc.) in combination with a MRI-compatible infusion pump (Harvard). MRI during infusion confirmed successful targeting and matched postmortem visualization of bromophenol blue. Assessment of the accuracy of the targeting revealed an overall 3D mean ± SD distance error of 1.2 ± 0.6 mm and angular distance error of 0.9 ± 0.5 mm. Our results in nonhuman primates confirm the accuracy of intraoperative MRI intracerebral navigation combined with an adaptable, pivot point-based targeting system and validates its use for preclinical intracerebral procedures.

Cellular interaction between the proximal and distal domains of the limb plays key roles in proximal-distal patterning. In Drosophila, these domains are established in the embryonic leg imaginal disc as a proximal domain expressing escargot, surrounding the Distal-less expressing distal domain in a circular pattern. The leg imaginal disc is derived from the limb primordium that also gives rise to the wing imaginal disc. We describe here essential roles of Wingless in patterning the leg imaginal disc. Firstly, Wingless signaling is essential for the recruitment of dorsal-proximal, distal, and ventral-proximal leg cells. Wingless requirement in the proximal leg domain appears to be unique to the embryo, since it was previously shown that Wingless signal transduction is not active in the proximal leg domain in larvae. Secondly, downregulation of Wingless signaling in wing disc is essential for its development, suggesting that Wg activity must be downregulated to separate wing and leg discs. In addition, we provide evidence that Dll restricts expression of a proximal leg-specific gene expression. We propose that those embryo-specific functions of Wingless signaling reflect its multiple roles in restricting competence of ectodermal cells to adopt the fate of thoracic appendages.