ABSTRACT
OBJECTIVE: Parkinsonian motor symptoms are linked to pathologically increased beta oscillations in the basal ganglia. Studies with externalised deep brain stimulation electrodes showed that Parkinson patients were able to rapidly gain control over these pathological basal ganglia signals through neurofeedback. Studies with fully implanted deep brain stimulation systems duplicating these promising results are required to grant transferability to daily application. METHODS: In this study, seven patients with idiopathic Parkinson's disease and one with familial Parkinson's disease were included. In a postoperative setting, beta oscillations from the subthalamic nucleus were recorded with a fully implanted deep brain stimulation system and converted to a real-time visual feedback signal. Participants were instructed to perform bidirectional neurofeedback tasks with the aim to modulate these oscillations. RESULTS: While receiving regular medication and deep brain stimulation, participants were able to significantly improve their neurofeedback ability and achieved a significant decrease of subthalamic beta power (median reduction of 31% in the final neurofeedback block). CONCLUSION: We could demonstrate that a fully implanted deep brain stimulation system can provide visual neurofeedback enabling patients with Parkinson's disease to rapidly control pathological subthalamic beta oscillations. SIGNIFICANCE: Fully-implanted DBS electrode-guided neurofeedback is feasible and can now be explored over extended timespans.
ABSTRACT
BACKGROUND: Enhancing slow waves, the electrophysiological (EEG) manifestation of non-rapid eye movement (NREM) sleep, could potentially benefit patients with Parkinson's disease (PD) by improving sleep quality and slowing disease progression. Phase-targeted auditory stimulation (PTAS) is an approach to enhance slow waves, which are detected in real-time in the surface EEG signal. OBJECTIVE: We aimed to test whether the local-field potential of the subthalamic nucleus (STN-LFP) can be used to detect frontal slow waves and assess the electrophysiological changes related to PTAS. METHODS: We recruited patients diagnosed with PD and undergoing Percept™ PC neurostimulator (Medtronic) implantation for deep brain stimulation of STN (STN-DBS) in a two-step surgery. Patients underwent three full-night recordings, including one between-surgeries recording and two during rehabilitation, one with DBS+ (on) and one with DBS- (off). Surface EEG and STN-LFP signals from Percept PC were recorded simultaneously, and PTAS was applied during sleep in all three recording sessions. RESULTS: Our results show that during NREM sleep, slow waves of the cortex and STN are time-locked. PTAS application resulted in power and coherence changes, which can be detected in STN-LFP. CONCLUSION: Our findings suggest the feasibility of implementing PTAS using solely STN-LFP signal for slow wave detection, thus without a need for an external EEG device alongside the implanted neurostimulator. Moreover, we propose options for more efficient STN-LFP signal preprocessing, including different referencing and filtering to enhance the reliability of cortical slow wave detection in STN-LFP recordings.
ABSTRACT
Respiratory rate (RR) is an often underestimated and underreported vital sign with tremendous clinical value. As a predictor of cardiopulmonary arrest, chronic obstructive pulmonary disease (COPD) exacerbation or indicator of health state for example in COVID-19 patients, respiratory rate could be especially valuable in remote long-term patient monitoring, which is challenging to implement. Contactless devices for home use aim to overcome these challenges. In this study, the contactless Sleepiz One+ respiration monitor for home use during sleep was validated against the thoracic effort belt. The agreement of instantaneous breathing rate and breathing rate statistics between the Sleepiz One+ device and the thoracic effort belt was initially evaluated during a 20-min sleep window under controlled conditions (no body movement) on a cohort of 19 participants and secondly in a more natural setting (uncontrolled for body movement) during a whole night on a cohort of 139 participants. Excellent agreement was shown for instantaneous breathing rate to be within 3 breaths per minute (Brpm) compared to thoracic effort band with an accuracy of 100% and mean absolute error (MAE) of 0.39 Brpm for the setting controlled for movement, and an accuracy of 99.5% with a MAE of 0.48 Brpm for the whole night measurement, respectively. Excellent agreement was also achieved for the respiratory rate statistics over the whole night with absolute errors of 0.43, 0.39 and 0.67 Brpm for the 10th, 50th and 90th percentiles, respectively. Based on these results we conclude that the Sleepiz One+ can estimate instantaneous respiratory rate and its summary statistics at high accuracy in a clinical setting. Further studies are required to evaluate the performance in the home environment, however, it is expected that the performance is at similar level, as the measurement conditions for the Sleepiz One+ device are better at home than in a clinical setting.
