Computer-Guided Deep Brain Stimulation Programming for Parkinson's Disease.

OBJECTIVE: Pilot study to evaluate computer-guided deep brain stimulation (DBS) programming designed to optimize stimulation settings using objective motion sensor-based motor assessments. MATERIALS AND METHODS: Seven subjects (five males; 54-71 years) with Parkinson's disease (PD) and recently implanted DBS systems participated in this pilot study. Within two months of lead implantation, the subject returned to the clinic to undergo computer-guided programming and parameter selection. A motion sensor was placed on the index finger of the more affected hand. Software guided a monopolar survey during which monopolar stimulation on each contact was iteratively increased followed by an automated assessment of tremor and bradykinesia. After completing assessments at each setting, a software algorithm determined stimulation settings designed to minimize symptom severities, side effects, and battery usage. RESULTS: Optimal DBS settings were chosen based on average severity of motor symptoms measured by the motion sensor. Settings chosen by the software algorithm identified a therapeutic window and improved tremor and bradykinesia by an average of 35.7% compared with baseline in the "off" state (p < 0.01). CONCLUSIONS: Motion sensor-based computer-guided DBS programming identified stimulation parameters that significantly improved tremor and bradykinesia with minimal clinician involvement. Automated motion sensor-based mapping is worthy of further investigation and may one day serve to extend programming to populations without access to specialized DBS centers.

Motor cortical representation of hand translation and rotation during reaching.

Previous studies have shown that hand translation is well represented by neuronal activity in the proximal arm area of primary motor cortex (M1). However, little is known about cortical representation of hand rotation in M1. In this study, single-unit activity was recorded from monkeys while they performed a "center-out with rotation" task. When reaching for a target, subjects had to match four separate kinematic parameters: three-dimensional location and one-dimensional orientation of the target. Among the 512 neurons modulated by hand movement, 446 were tuned to hand translation, 326 were tuned to hand rotation, and 260 neurons were tuned to both hand translation and hand rotation. Approximately half of the neurons that encoded both translation and rotation did so in a nonlinear manner. This nonlinear interaction can be modeled as a gain-field type of encoding whereby hand rotational velocity modulated the hand translational cosine tuning curves in a multiplicative manner. Furthermore, this study demonstrated that both hand translation and hand rotation can be decoded simultaneously from a population of motor cortical neurons.

Differential response of speed, amplitude, and rhythm to dopaminergic medications in Parkinson's disease.

Although movement impairment in Parkinson's disease includes slowness (bradykinesia), decreased amplitude (hypokinesia), and dysrhythmia, clinicians are instructed to rate them in a combined 0-4 severity scale using the Unified Parkinson's Disease Rating Scale motor subscale. The objective was to evaluate whether bradykinesia, hypokinesia, and dysrhythmia are associated with differential motor impairment and response to dopaminergic medications in patients with Parkinson's disease. Eighty five Parkinson's disease patients performed finger-tapping (item 23), hand-grasping (item 24), and pronation-supination (item 25) tasks OFF and ON medication while wearing motion sensors on the most affected hand. Speed, amplitude, and rhythm were rated using the Modified Bradykinesia Rating Scale. Quantitative variables representing speed (root mean square angular velocity), amplitude (excursion angle), and rhythm (coefficient of variation) were extracted from kinematic data. Fatigue was measured as decrements in speed and amplitude during the last 5 seconds compared with the first 5 seconds of movement. Amplitude impairments were worse and more prevalent than speed or rhythm impairments across all tasks (P < .001); however, in the ON state, speed scores improved exclusively by clinical (P < 10(-6) ) and predominantly by quantitative (P < .05) measures. Motor scores from OFF to ON improved in subjects who were strictly bradykinetic (P < .01) and both bradykinetic and hypokinetic (P < 10(-6) ), but not in those strictly hypokinetic. Fatigue in speed and amplitude was not improved by medication. Hypokinesia is more prevalent than bradykinesia, but dopaminergic medications predominantly improve the latter. Parkinson's disease patients may show different degrees of impairment in these movement components, which deserve separate measurement in research studies. © 2011 Movement Disorder Society.

The modified bradykinesia rating scale for Parkinson's disease: reliability and comparison with kinematic measures.

Bradykinesia encompasses slowness, decreased movement amplitude, and dysrhythmia. Unified Parkinson's Disease Rating Scale-based bradykinesia-related items require that clinicians condense abnormalities in speed, amplitude, fatiguing, hesitations, and arrests into a single score. The objective of this study was to evaluate the reliability of a modified bradykinesia rating scale, which separately assesses speed, amplitude, and rhythm and its correlation with kinematic measures from motion sensors. Fifty patients with Parkinson's disease performed Unified Parkinson's Disease Rating Scale-directed finger tapping, hand grasping, and pronation-supination while wearing motion sensors. Videos were rated blindly and independently by 4 clinicians. The modified bradykinesia rating scale and Unified Parkinson's Disease Rating Scale demonstrated similar inter- and intrarater reliability. Raters placed greater weight on amplitude than on speed or rhythm when assigning a Unified Parkinson's Disease Rating Scale score. Modified bradykinesia rating scale scores for speed, amplitude, and rhythm correlated highly with quantitative kinematic variables. The modified bradykinesia rating scale separately captures bradykinesia components with interrater and intrarater reliability similar to that of the Unified Parkinson's Disease Rating Scale. Kinematic sensors can accurately quantify speed, amplitude, and rhythm to aid in the development and evaluation of novel therapies in Parkinson's disease.

Real-World Evidence for a Smartwatch-Based Parkinson's Motor Assessment App for Patients Undergoing Therapy Changes.

INTRODUCTION: Parkinson's disease (PD) is poorly quantified by patients outside the clinic, and paper diaries have problems with subjective descriptions and bias. Wearable sensor platforms; however, can accurately quantify symptoms such as tremor, dyskinesia, and bradykinesia. Commercially available smartwatches are equipped with accelerometers and gyroscopes that can measure motion for objective evaluation. We sought to evaluate the clinical utility of a prescription smartwatch-based monitoring system for PD utilizing periodic task-based motor assessment. METHODS: Sixteen patients with PD used a smartphone- and smartwatch-based monitoring system to objectively assess motor symptoms for 1 week prior to instituting a doctor recommended change in therapy and for 4 weeks after the change. After 5 weeks the participants returned to the clinic to discuss their results with their doctor, who made therapy recommendations based on the reports and his clinical judgment. Symptom scores were synchronized with the medication diary and the temporal effects of therapy on weekly and hourly timescales were calculated. RESULTS: Thirteen participants successfully completed the study and averaged 4.9 assessments per day for 3 days per week during the study. The doctor instructed 8 participants to continue their new regimens and 5 to revert to their previous regimens. The smartwatch-based assessments successfully captured intraday fluctuations and short- and long-term responses to therapies, including detecting significant improvements (p < 0.05) in at least one symptom in 7 participants. CONCLUSIONS: The smartwatch-based app successfully captured temporal trends in symptom scores following application of new therapy on hourly, daily, and weekly timescales. These results suggest that validated smartwatch-based PD monitoring can provide clinically relevant information and may reduce the need for traditional office visits for therapy adjustment.

Local field potentials for BCI control.

The gold standard in brain-computer interface (BCI) modalities is multi single-unit recordings in the primary motor cortex. It yields the fastest and most elegant control (i.e., most degrees of freedom and bitrate). Unfortunately, single-unit electrodes are prone to encapsulation, which limit their single-unit recording life. However, encapsulation does not significantly affect intracortical local field potentials (LFPs). LFPs and single-unit activity were recorded from the motor cortices of three monkeys (Macaca fascicularis) while they performed a standard 3D center-out reaching task and a 3D circle-drawing task. The high frequency (HF) (60-200 Hz) spectral amplitudes of a subset of the LFPs were found to be directionally tuned much like single units. In fact, stable isolation of single units on the same electrode increased the likelihood that the HF-LFP would be significantly cosine tuned to hand direction. The presence of significantly tuned single units further increased the likelihood of a tuned HF-LFP, suggesting that this band of HF-LFP activity is at least partially generated by local neuronal action potential currents (i.e., single-unit activity). Given that encapsulation makes recording single units over a long period of time difficult, these results suggest that HF-LFPs may be a more stable and efficient method of monitoring neural activity for BCI applications.

Clinically deployable Kinesia technology for automated tremor assessment.

The objective was to design, build, and assess Kinesia, a wireless system for automated assessment of Parkinson's disease (PD) tremor. The current standard in evaluating PD is the Unified Parkinson's Disease Rating Scale (UPDRS), a qualitative ranking system typically completed during an office visit. Kinesia integrates accelerometers and gyroscopes in a compact patient-worn unit to capture kinematic movement disorder features. Objectively quantifying PD manifestations with increased time resolution should aid in evaluating efficacy of treatment protocols and improve patient management. In this study, PD subjects performed the tremor subset of the UPDRS motor section while wearing Kinesia. Quantitative kinematic features were processed and highly correlated to clinician scores for rest tremor (r(2) = 0.89), postural tremor (r(2) = 0.90), and kinetic tremor (r(2) = 0.69). The quantitative features were used to develop a mathematical model that predicted tremor severity scores for new data with low errors. Finally, PD subjects indicated high clinical acceptance.

Continuous Assessment of Levodopa Response in Parkinson's Disease Using Wearable Motion Sensors.

OBJECTIVE: Fluctuations in response to levodopa in Parkinson's disease (PD) are difficult to treat as tools to monitor temporal patterns of symptoms are hampered by several challenges. The objective was to use wearable sensors to quantify the dose response of tremor, bradykinesia, and dyskinesia in individuals with PD. METHODS: Thirteen individuals with PD and fluctuating motor benefit were instrumented with wrist and ankle motion sensors and recorded by video. Kinematic data were recorded as subjects completed a series of activities in a simulated home environment through transition from off to on medication. Subjects were evaluated using the unified Parkinson disease rating scale motor exam (UPDRS-III) at the start and end of data collection. Algorithms were applied to the kinematic data to score tremor, bradykinesia, and dyskinesia. A blinded clinician rated severity observed on video. Accuracy of algorithms was evaluated by comparing scores with clinician ratings using a receiver operating characteristic (ROC) analysis. RESULTS: Algorithm scores for tremor, bradykinesia, and dyskinesia agreed with clinician ratings of video recordings (ROC area > 0.8). Summary metrics extracted from time intervals before and after taking medication provided quantitative measures of therapeutic response (p < 0.01). Radar charts provided intuitive visualization, with graphical features correlated with UPDRS-III scores (R = 0.81). CONCLUSION: A system with wrist and ankle motion sensors can provide accurate measures of tremor, bradykinesia, and dyskinesia as patients complete routine activities. SIGNIFICANCE: This technology could provide insight on motor fluctuations in the context of daily life to guide clinical management and aid in development of new therapies.

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.

App-Based Bradykinesia Tasks for Clinic and Home Assessment in Parkinson's Disease: Reliability and Responsiveness.

BACKGROUND: Clinical rating of bradykinesia in Parkinson disease (PD) is challenging as it must combine several movement features into a single score. Additionally, in-clinic assessment cannot capture fluctuations throughout the day. OBJECTIVE: To evaluate the reliability and responsiveness of a motion sensor-based tablet app for objective bradykinesia assessment in clinic and at home as compared to clinical ratings. METHODS: Thirty-two PD patients treated with subthalamic deep brain stimulation (DBS) were outfitted with a motion sensor on the index finger of the more affected hand to perform two repetitions of finger-tapping, hand opening-closing, and arm pronation-supination tasks with DBS on and 10, 20, and 30 minutes after turning DBS off. Tasks were videotaped for blinded clinician rating using the Modified Bradykinesia Rating Scale (MBRS). Participants were then sent home with an app-based system to perform two repetitions of the same tasks six times per day spaced two hours apart, three days per week, for two weeks. Intraclass correlation (ICC) and minimal detectable change (MDC) were calculated. RESULTS: As the effects of DBS wore off, motion sensors detected worsening of amplitude sooner than did clinician-rated MBRS for all three tasks. ICCs were significantly higher and MDCs were significantly lower for motion sensors in the clinic and at home than for clinician ratings (p < 0.01). CONCLUSIONS: The tablet-based app demonstrated higher reliability and responsiveness in capturing bradykinesia-related tasks in the clinic and at home than did clinician ratings. This tool may enhance the assessment of novel therapies.

Local field potential spectral tuning in motor cortex during reaching.

In this paper, intracortical local field potentials (LFPs) and single units were recorded from the motor cortices of monkeys (Macaca fascicularis) while they preformed a standard three-dimensional (3-D) center-out reaching task. During the center-out task, the subjects held their hands at the location of a central target and then reached to one of eight peripheral targets forming the corners of a virtual cube. The spectral amplitudes of the recorded LFPs were calculated, with the high-frequency LFP (HF-LFP) defined as the average spectral amplitude change from baseline from 60 to 200 Hz. A 3-D linear regression across the eight center-out targets revealed that approximately 6% of the beta LFPs (18-26 Hz) and 18% of the HF-LFPs were tuned for velocity (p-value < 0.05), while 10% of the beta LFPs and 15% of the HF-LFPs were tuned for position. These results suggest that a multidegree-of-freedom brain-machine interface is possible using high-frequency LFP recordings in motor cortex.

Wearable Sensors for Advanced Therapy Referral in Parkinson's Disease.

BACKGROUND: Advanced therapies, such as deep brain stimulation and levodopa-carbidopa intestinal gel, can significantly improve quality of life in advanced Parkinson's disease (PD). However, determining who should be referred for advanced therapy is a challenging problem. OBJECTIVE: The objective was to determine the impact of remote monitoring using objective, wearable sensors on the advanced therapy referral rate in patients with advanced PD and if sensor data differed in patients who were referred and those who were not. METHODS: A retrospective, exploratory, secondary analysis was performed on data collected in a study that followed forty individuals with advanced PD for one year with half receiving standard care and half using motion sensor-based remote monitoring once per month in conjunction with standard care. Advanced therapy referral rates were compared between groups. For the group who underwent remote monitoring, objective motor features representing symptoms, dyskinesias, and fluctuations were examined to determine if objective kinematic features differed between patients who were and were not recommended for advanced therapy. RESULTS: The advanced therapy referral rate was significantly higher for patients when a clinician had access to remote monitoring reports compared to standard care alone (63.6% versus 11.8%, p < 0.01). Bradykinesia severity, bradykinesia fluctuations, and dyskinesia severity differed significantly (p < 10e-8, p < 10e-5, and p < 0.01, respectively) between patients recommended and not recommended for advanced therapy. CONCLUSIONS: Remote monitoring technologies can capture motor features that may be clinically useful in identifying patients who may be candidates for advanced therapy. This could lead to development of automated screening algorithms, improve referral efficiency, and expand access to advanced therapies for patients with advanced PD.

Motion sensor strategies for automated optimization of deep brain stimulation in Parkinson's disease.

BACKGROUND: Deep brain stimulation (DBS) is a well-established treatment for Parkinson's disease (PD). Optimization of DBS settings can be a challenge due to the number of variables that must be considered, including presence of multiple motor signs, side effects, and battery life. METHODS: Nine PD subjects visited the clinic for programming at approximately 1, 2, and 4 months post-surgery. During each session, various stimulation settings were assessed and subjects performed motor tasks while wearing a motion sensor to quantify tremor and bradykinesia. At the end of each session, a clinician determined final stimulation settings using standard practices. Sensor-based ratings of motor symptom severities collected during programming were then used to develop two automated programming algorithms--one to optimize symptom benefit and another to optimize battery life. Therapeutic benefit was compared between the final clinician-determined DBS settings and those calculated by the automated algorithm. RESULTS: Settings determined using the symptom optimization algorithm would have reduced motor symptoms by an additional 13 percentage points when compared to clinician settings, typically at the expense of increased stimulation amplitude. By adding a battery life constraint, the algorithm would have been able to decrease stimulation amplitude by an average of 50% while maintaining the level of therapeutic benefit observed using clinician settings for a subset of programming sessions. CONCLUSIONS: Objective assessment in DBS programming can identify settings that improve symptoms or obtain similar benefit as clinicians with improvement in battery life. Both options have the potential to improve post-operative patient outcomes.

Clinician versus machine: reliability and responsiveness of motor endpoints in Parkinson's disease.

BACKGROUND: Enhancing the reliability and responsiveness of motor assessments required to demonstrate therapeutic efficacy is a priority for Parkinson's disease (PD) clinical trials. The objective of this study is to determine the reliability and responsiveness of a portable kinematic system for quantifying PD motor deficits as compared to clinical ratings. METHODS: Eighteen PD patients with subthalamic nucleus deep-brain stimulation (DBS) performed three tasks for evaluating resting tremor, postural tremor, and finger-tapping speed, amplitude, and rhythm while wearing a wireless motion-sensor unit (Kinesia) on the more-affected index finger. These tasks were repeated three times with DBS turned off and at each of 10 different stimulation amplitudes chosen to yield small changes in treatment response. Each task performance was video-recorded for subsequent clinician rating in blinded, randomized order. Test-retest reliability was calculated as intraclass correlation (ICC) and sensitivity was calculated as minimal detectable change (MDC) for each DBS amplitude. RESULTS: ICCs for Kinesia were significantly higher than those for clinician ratings of finger-tapping speed (p < 0.0001), amplitude (p < 0.0001), and rhythm (p < 0.05), but were not significantly different for evaluations of resting or postural tremor. Similarly, Kinesia scores yielded a lower MDC as compared with clinician scores across all finger-tapping subscores (p < 0.0001), but did not differ significantly for resting and postural tremor. CONCLUSIONS: The Kinesia portable kinematic system can provide greater test-retest reliability and sensitivity to change than conventional clinical ratings for measuring bradykinesia, hypokinesia, and dysrhythmia in PD patients.

Motion sensor dyskinesia assessment during activities of daily living.

BACKGROUND: Dyskinesia throughout the levodopa dose cycle has been previously measured in patients with Parkinson's disease (PD) using a wrist-worn motion sensor during the stationary tasks of arms resting and extended. Quantifying dyskinesia during unconstrained activities poses a unique challenge since these involuntary movements are kinematically similar to voluntary movement. OBJECTIVE: To determine the feasibility of using motion sensors to measure dyskinesia during activities of daily living. METHODS: Fifteen PD subjects performed scripted activities of daily living while wearing motion sensors on bilateral hands, thighs, and ankles over the course of a levodopa dose cycle. Videos were scored by clinicians using the modified Abnormal Involuntary Movement Scale to rate dyskinesia severity in separate body regions, with the total score used as an overall measure. Kinematic features were extracted from the motion data and algorithms were generated to output severity scores. RESULTS: Movements when subjects were experiencing dyskinesia were less smooth than when they were not experiencing dyskinesia. Dyskinesia scores predicted by the model using all sensors were highly correlated with clinician scores, with a correlation coefficient of 0.86 and normalized root-mean-square-error of 7.4%. Accurate predictions were maintained when two sensors on the most affected side of the body (one on the upper extremity and one on the lower extremity) were used. CONCLUSIONS: A system with motion sensors may provide an accurate measure of overall dyskinesia that can be used to monitor patients as they complete typical activities, and thus provide insight on symptom fluctuation in the context of daily life.

Development of a clinician worn device for the evaluation of abnormal muscle tone.

Neurological disorders such as cerebral palsy commonly result in abnormal muscle hyperactivity that negatively effects functional use of the affected limbs. Individuals with cerebral palsy often present with a mix of spasticity and dystonia, and it can be difficult to distinguish between the effects of these types of abnormal tone. Different types of abnormal tone respond differently to treatments such as deep brain stimulation and baclofen. Conventional clinical evaluation techniques provide minimal information for distinguishing abnormal tone characteristics and changes from treatment. Devices that quantify abnormal tone characteristics can help distinguish between the effects of different types of abnormal muscle tone, and help to quantify treatment effects. This paper discusses the development and initial evaluation of MyoSense(TM), a clinician worn device for the quantification and differentiation of abnormal muscle tone. MyoSense evaluates the orientation, speed, and force during clinician manipulation of the affected limbs with a protocol that is similar to conventional practice for evaluating abnormal tone. Evaluation of the MyoSense device, using a mechanical apparatus to simulate abnormal muscle tone, showed good resolution of abnormal tone characteristics. Using a procedure directly modeled after conventional clinical evaluation of abnormal tone, MyoSense data showed good correlation with simulated profiles, 0.8 for spasticity and 0.93 for hypertonia. Evaluation of average change across different limb manipulation speeds, to mitigate acceleration and mechanical effects, resulted in MyoSense data correlations to simulated profiles of 0.99 for spasticity, spasticity with a catch, and dystonia. Overall these results show promise for future clinical evaluation of the MyoSense device.

Feasibility of home-based automated Parkinson's disease motor assessment.

Patients with Parkinson's disease (PD) receive therapies aimed at addressing a diverse range of motor symptoms. Motor complications in the form of symptom fluctuations and dyskinesias that commonly occur with chronic PD medication use may not be effectively captured by Unified Parkinson's Disease Rating Scale (UPDRS) assessments performed in the clinic. Therefore, home monitoring may be a viable adjunct tool to provide insight into PD motor symptom response to treatment. In this pilot study, we sought to evaluate the feasibility of capturing PD motor symptoms at home using a computer-based assessment system. Ten subjects diagnosed with idiopathic PD used the system at home and ten non-PD control subjects used the system in a laboratory. The Kinesia system consists of a wireless finger-worn motion sensor and a laptop computer with software for automated tremor and bradykinesia severity score assessments. Data from control subjects were used to develop compliance algorithms for rejecting motor tasks performed incorrectly. These algorithms were then applied to data collected from the PD subjects who used the Kinesia system at home to complete motor exams 3-6 times per day over 3-6 days. Motor tasks not rejected by the compliance algorithms were further processed for symptom severity. PD subjects successfully completed motor assessments at home, with approximately 97% of all motor task data files (1222/1260) accepted. These findings suggest that objective home monitoring of PD motor fluctuations is feasible.

Automated motion sensor quantification of gait and lower extremity bradykinesia.

The objective was to develop and evaluate algorithms for quantifying gait and lower extremity bradykinesia in patients with Parkinson's disease using kinematic data recorded on a heel-worn motion sensor unit. Subjects were evaluated by three movement disorder neurologists on four domains taken from the Movement Disorders Society Unified Parkinson's Disease Rating Scale while wearing the motion sensor unit. Multiple linear regression models were developed based on the recorded kinematic data and clinician scores and produced outputs highly correlated to clinician scores with an average correlation coefficient of 0.86. The newly developed models have been integrated into a home-based system for monitoring Parkinson's disease motor symptoms.