Benchmarking Real-Time Algorithms for In-Phase Auditory Stimulation of Low Amplitude Slow Waves With Wearable EEG Devices During Sleep

• Published in: IEEE transactions on biomedical engineering Vol. 69; no. 9; pp. 2916 - 2925
• Main Authors: Ferster, Maria Laura, Da Poian, Giulia, Menachery, Kiran, Schreiner, Simon J., Lustenberger, Caroline, Maric, Angelina, Huber, Reto, Baumann, Christian R., Karlen, Walter
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.09.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adults; Algorithms; Amplitudes; Auditory stimulation; autonomous medical devices; Cognitive ability; EEG; Electroencephalography; Microcontrollers; Movement disorders; Neurodegeneration; Neurodegenerative diseases; neuromodulation; Older adults; Older people; Parkinson; Parkinson's disease; Phase estimation; Phase frequency detectors; Phase locked loops; phase tracking; phase vocoder; PLL; Real time; Real-time systems; Sleep; Stimulation; Tracking; wearable; Wearable technology
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2022.3157468

Objective: In-phase stimulation of EEG slow waves (SW) during deep sleep has shown to improve cognitive function. SW enhancement is particularly desirable in subjects with low-amplitude SW such as older adults or patients suffering from neurodegeneration. However, existing algorithms to estimate the up-phase of EEG suffer from a poor phase accuracy at low amplitudes and when SW frequencies are not constant. Methods: We introduce two novel algorithms for real-time EEG phase estimation on autonomous wearable devices, a phase-locked loop (PLL) and, for the first time, a phase vocoder (PV). We compared these phase tracking algorithms with a simple amplitude threshold approach. The optimized algorithms were benchmarked for phase accuracy, the capacity to estimate phase at SW amplitudes between 20 and 60 μV, and SW frequencies above 1 Hz on 324 home-based recordings from healthy older adults and Parkinson disease (PD) patients. Furthermore, the algorithms were implemented on a wearable device and the computational efficiency and the performance was evaluated in simulation and with a PD patient. Results: All three algorithms delivered more than 70% of the stimulation triggers during the SW up-phase. The PV showed the highest capacity on targeting low-amplitude SW and SW with frequencies above 1 Hz. The hardware testing revealed that both PV and PLL have marginal impact on microcontroller load, while the efficiency of the PV was 4% lower. Active stimulation did not influence the phase tracking. Conclusion: This work demonstrated that phase-accurate auditory stimulation can also be delivered during fully remote sleep interventions in populations with low-amplitude SW.