Telehealth Management of Parkinson's Disease Using Wearable Sensors: An Exploratory Study.

BACKGROUND: Parkinson's disease (PD) motor symptoms can fluctuate and may not be accurately reflected during a clinical evaluation. In addition, access to movement disorder specialists is limited for many with PD. The objective was to assess the impact of motion sensor-based telehealth diagnostics on PD clinical care and management. METHODS: Eighteen adults with PD were randomized to control or experimental groups. All participants were instructed to use a motion sensor-based monitoring system at home one day per week, for seven months. The system included a finger-worn motion sensor and tablet-based software interface that guided patients through tasks to quantify tremor, bradykinesia, and dyskinesia. Data were processed into motor symptom severity reports, which were reviewed by a movement disorders neurologist for experimental group participants. After three months and six months, control group participants visited the clinic for a routine appointment, while experimental group participants had a videoconference or phone call instead. RESULTS: Home based assessments were completed with median compliance of 95.7%. For a subset of participants, the neurologist successfully used information in the reports such as quantified response to treatment or progression over time to make therapy adjustments. Changes in clinical characteristics from study start to end were not significantly different between groups. DISCUSSION: Individuals with PD were able and willing to use remote monitoring technology. Patient management aided by telehealth diagnostics provided comparable outcomes to standard care. Telehealth technologies combined with wearable sensors have the potential to improve care for disparate PD populations or those unable to travel.

Wearable Sensors in Huntington Disease: A Pilot Study.

BACKGROUND: The Unified Huntington's Disease Rating Scale (UHDRS) is the principal means of assessing motor impairment in Huntington disease but is subjective and generally limited to in-clinic assessments. OBJECTIVE: To evaluate the feasibility and ability of wearable sensors to measure motor impairment in individuals with Huntington disease in the clinic and at home. METHODS: Participants with Huntington disease and controls were asked to wear five accelerometer-based sensors attached to the chest and each limb for standardized, in-clinic assessments and for one day at home. A second chest sensor was worn for six additional days at home. Gait measures were compared between controls, participants with Huntington disease, and participants with Huntington disease grouped by UHDRS total motor score using Cohen's d values. RESULTS: Fifteen individuals with Huntington disease and five controls completed the study. Sensor data were successfully captured from 18 of the 20 participants at home. In the clinic, the standard deviation of step time (time between consecutive steps) was increased in Huntington disease (p < 0.0001; Cohen's d = 2.61) compared to controls. At home with additional observations, significant differences were observed in seven additional gait measures. The gait of individuals with higher total motor scores (50 or more) differed significantly from those with lower total motor scores (below 50) on multiple measures at home. CONCLUSIONS: In this pilot study, the use of wearable sensors in clinic and at home was feasible and demonstrated gait differences between controls, participants with Huntington disease, and participants with Huntington disease grouped by motor impairment.

Novel methods and technologies for 21st-century clinical trials: a review.

IMPORTANCE: New technologies are rapidly reshaping health care. However, their effect on drug development to date generally has been limited. OBJECTIVES: To evaluate disease modeling and simulation, alternative study design, novel objective measures, virtual research visits, and enhanced participant engagement and to examine their potential effects as methods and tools on clinical trials. EVIDENCE REVIEW: We conducted a systematic search of relevant terms on PubMed (disease modeling and clinical trials; adaptive design, clinical trials, and neurology; Internet, clinical trials, and neurology; and telemedicine, clinical trials, and neurology), references of previous publications, and our files. The search encompassed articles published from January 1, 2000, through November 30, 2014, and produced 7976 articles, of which 22 were determined to be relevant and are included in this review. FINDINGS: Few of these new methods and technologies have been applied to neurology clinical trials. Clinical outcomes, including cognitive and stroke outcomes, increasingly are captured remotely. Other therapeutic areas have successfully implemented many of these tools and technologies, including web-enabled clinical trials. CONCLUSIONS AND RELEVANCE: Increased use of new tools and approaches in future clinical trials can enhance the design, improve the assessment, and engage participants in the evaluation of novel therapies for neurologic disorders.