A palm-worn device to quantify rigidity in Parkinson's disease.

BACKGROUND: Parkinsonian rigidity is identified on clinical examination as resistance to passive movement. Measurement of rigidity commonly relies on ordinal rating scales (MDS-UPDRS), however instrumented objective measures may provide greater mechanistic insight. NEW METHOD: We present a palm-worn instrument to objectively quantify rigidity on a continuous scale. The device employs a miniature motor to flex the third digit of the hand about the metacarpophalangeal joint whilst transducers record flexion/extension forces. We aim to determine congruence with the MDS-UPDRS, investigate sensitivity to the impact of deep brain stimulation (DBS) and contralateral movement, and make comparisons with healthy individuals. Eight participants with Parkinson's disease underwent evaluation during conditions: on and off DBS, and with and without contralateral limb movement to activate rigidity. During each DBS condition, wash-in/out effects were tracked using both our instrument and two blinded clinical raters. Sixteen healthy volunteers (age-matched/young) served as controls. RESULTS: Rigidity measured using our instrument had moderate agreement with the MDS-UPDRS and showed differences between therapeutic state, activation conditions, and disease/healthy cohorts. Rigidity gradually worsened over a one-hour period after DBS cessation, but improved more rapidly with DBS resumption. COMPARISON WITH EXISTING METHODS: Previous attempts to quantify rigidity include manual approaches where a clinician is required to manipulate limbs while sensors passively gather information, or large automated instruments to move the wrist or elbow. CONCLUSION: Given its ability to track changes in rigidity due to therapeutic intervention, our technique could have applications where continuous measurement is required or where a suitably qualified rater is absent.

Objective evaluation of bradykinesia in Parkinson's disease using an inexpensive marker-less motion tracking system.

OBJECTIVE: Quantification of bradykinesia (slowness of movement) is crucial for the treatment and monitoring of Parkinson's disease. Subjective observational techniques are the de-facto 'gold standard', but such clinical rating scales suffer from poor sensitivity and inter-rater variability. Although various technologies have been developed for assessing bradykinesia in recent years, most still require considerable expertise and effort to operate. Here we present a novel method to utilize an inexpensive off-the-shelf hand-tracker (Leap Motion) to quantify bradykinesia. APPROACH: Eight participants with Parkinson's disease receiving benefit from deep brain stimulation were recruited for the study. Participants were assessed 'on' and 'off' stimulation, with the 'on' condition repeated to evaluate reliability. Participants performed wrist pronation/supination, hand open/close, and finger-tapping tasks during each condition. Tasks were simultaneously captured by our software and rated by three clinicians. A linear regression model was developed to predict clinical scores and its performance was assessed with leave-one-subject-out cross validation. MAIN RESULTS: Aggregate bradykinesia scores predicted by our method were in strong agreement (R = 0.86) with clinical scores. The model was able to differentiate therapeutic states and comparison between the test-retest conditions yielded no significant difference (p  = 0.50). SIGNIFICANCE: These findings demonstrate that our method can objectively quantify bradykinesia in agreement with clinical observation and provide reliable measurements over time. The hardware is readily accessible, requiring only a modest computer and our software to perform assessments, thus making it suitable for both clinic- and home-based symptom tracking.

Balance control systems in Parkinson's disease and the impact of pedunculopontine area stimulation.

Impaired balance is a major contributor to falls and diminished quality of life in Parkinson's disease, yet the pathophysiology is poorly understood. Here, we assessed if patients with Parkinson's disease and severe clinical balance impairment have deficits in the intermittent and continuous control systems proposed to maintain upright stance, and furthermore, whether such deficits are potentially reversible, with the experimental therapy of pedunculopontine nucleus deep brain stimulation. Two subject groups were assessed: (i) 13 patients with Parkinson's disease and severe clinical balance impairment, implanted with pedunculopontine nucleus deep brain stimulators; and (ii) 13 healthy control subjects. Patients were assessed in the OFF medication state and blinded to two conditions; off and on pedunculopontine nucleus stimulation. Postural sway data (deviations in centre of pressure) were collected during quiet stance using posturography. Intermittent control of sway was assessed by calculating the frequency of intermittent switching behaviour (discontinuities), derived using a wavelet-based transformation of the sway time series. Continuous control of sway was assessed with a proportional-integral-derivative (PID) controller model using ballistic reaction time as a measure of feedback delay. Clinical balance impairment was assessed using the 'pull test' to rate postural reflexes and by rating attempts to arise from sitting to standing. Patients with Parkinson's disease demonstrated reduced intermittent switching of postural sway compared with healthy controls. Patients also had abnormal feedback gains in postural sway according to the PID model. Pedunculopontine nucleus stimulation improved intermittent switching of postural sway, feedback gains in the PID model and clinical balance impairment. Clinical balance impairment correlated with intermittent switching of postural sway (rho = - 0.705, P < 0.001) and feedback gains in the PID model (rho = 0.619, P = 0.011). These results suggest that dysfunctional intermittent and continuous control systems may contribute to the pathophysiology of clinical balance impairment in Parkinson's disease. Clinical balance impairment and their related control system deficits are potentially reversible, as demonstrated by their improvement with pedunculopontine nucleus deep brain stimulation.

Clinical validation of a precision electromagnetic tremor measurement system in participants receiving deep brain stimulation for essential tremor.

Tremor is characterized commonly through subjective clinical rating scales. Accelerometer-based techniques for objective tremor measurement have been developed in the past, yet these measures are usually presented as an unintuitive dimensionless index without measurement units. Here we have developed a tool (TREMBAL) to provide quantifiable and objective measures of tremor severity using electromagnetic motion tracking. We aimed to compare TREMBAL's objective measures with clinical tremor ratings and determine the test-retest reliability of our technique. Eight participants with ET receiving deep brain stimulation (DBS) therapy were consented. Tremor was simultaneously recorded using TREMBAL and video during DBS adjustment. After each adjustment, participants performed a hands-outstretched task (for postural tremor) and a finger-nose task (for kinetic tremor). Video recordings were de-identified, randomized, and shown to a panel of movement disorder specialists to obtain their ratings. Regression analysis and Pearson's correlations were used to determine agreement between datasets. Subsets of the trial were repeated to assess test-retest reliability. Tremor amplitude and velocity measures were in close agreement with mean clinical ratings (r > 0.90) for both postural and kinetic tremors. Test-retest reliability for both translational and rotational components of tremor showed intra-class correlations >0.80. TREMBAL assessments showed that tremor gradually improved with increasing DBS therapy-this was also supported by clinical observation. TREMBAL measurements are a sensitive, objective and reliable assessment of tremor severity. This tool may have application in clinical trials and in aiding automated optimization of deep brain stimulation.