A comprehensive study on the efficacy of a wearable sleep aid device featuring closed-loop real-time acoustic stimulation.

Difficulty falling asleep is one of the typical insomnia symptoms. However, intervention therapies available nowadays, ranging from pharmaceutical to hi-tech tailored solutions, remain ineffective due to their lack of precise real-time sleep tracking, in-time feedback on the therapies, and an ability to keep people asleep during the night. This paper aims to enhance the efficacy of such an intervention by proposing a novel sleep aid system that can sense multiple physiological signals continuously and simultaneously control auditory stimulation to evoke appropriate brain responses for fast sleep promotion. The system, a lightweight, comfortable, and user-friendly headband, employs a comprehensive set of algorithms and dedicated own-designed audio stimuli. Compared to the gold-standard device in 883 sleep studies on 377 subjects, the proposed system achieves (1) a strong correlation (0.89 ± 0.03) between the physiological signals acquired by ours and those from the gold-standard PSG, (2) an 87.8% agreement on automatic sleep scoring with the consensus scored by sleep technicians, and (3) a successful non-pharmacological real-time stimulation to shorten the duration of sleep falling by 24.1 min. Conclusively, our solution exceeds existing ones in promoting fast falling asleep, tracking sleep state accurately, and achieving high social acceptance through a reliable large-scale evaluation.

Scalable and modular wireless-network infrastructure for large-scale behavioural neuroscience.

The use of rodents to acquire understanding of the function of neural circuits and of the physiological, genetic and developmental underpinnings of behaviour has been constrained by limitations in the scalability, automation and high-throughput operation of implanted wireless neural devices. Here we report scalable and modular hardware and software infrastructure for setting up and operating remotely programmable miniaturized wireless networks leveraging Bluetooth Low Energy for the study of the long-term behaviour of large groups of rodents. The integrated system allows for automated, scheduled and real-time experimentation via the simultaneous and independent use of multiple neural devices and equipment within and across laboratories. By measuring the locomotion, feeding, arousal and social behaviours of groups of mice or rats, we show that the system allows for bidirectional data transfer from readily available hardware, and that it can be used with programmable pharmacological or optogenetic stimulation. Scalable and modular wireless-network infrastructure should facilitate the remote operation of fully automated large-scale and long-term closed-loop experiments for the study of neural circuits and animal behaviour.

Epileptic Seizure Detection and Experimental Treatment: A Review.

One-fourths of the patients have medication-resistant seizures and require seizure detection and treatment continuously to cope with sudden seizures. Seizures can be detected by monitoring the brain and muscle activities, heart rate, oxygen level, artificial sounds, or visual signatures through EEG, EMG, ECG, motion, or audio/video recording on the human head and body. In this article, we first discuss recent advances in seizure sensing, signal processing, time- or frequency-domain analysis, and classification algorithms to detect and classify seizure stages. Then, we show a strong potential of applying recent advancements in non-invasive brain stimulation technology to treat seizures. In particular, we explain the fundamentals of brain stimulation approaches, including (1) transcranial magnetic stimulation (TMS), (2) transcranial direct current stimulation (tDCS), (3) transcranial focused ultrasound stimulation (tFUS), and how to use them to treat seizures. Through this review, we intend to provide a broad view of both recent seizure diagnoses and treatments. Such knowledge would help fresh and experienced researchers to capture the advancements in sensing, detection, classification, and treatment seizures. Last but not least, we provide potential research directions that would attract seizure researchers/engineers in the field.