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1.
Artículo en Inglés | MEDLINE | ID: mdl-38083730

RESUMEN

Providing clinicians with objective outcomes of neuromodulation therapy is a key unmet need, especially in emerging areas such as epilepsy and mood disorders. These diseases have episodic behavior and circadian/multidien rhythm characteristics that are difficult to capture in short clinical follow-ups. This work presents preliminary validation evidence for an implantable neuromodulation system with integrated physiological event monitoring, with an initial focus on seizure tracking for epilepsy. The system was developed to address currently unmet requirements for patients undergoing neuromodulation therapy for neurological disorders, specifically the ability to sense physiological data during stimulation and track events with seconds-level granularity. The system incorporates an interactive software tool to enable optimal configuration of the signal processing chain on an embedded implantable device (the Picostim-DyNeuMo Mk-2) including data ingestion from the device loop recorder, event labeling, generation of filter and classification parameters, as well as summary statistics. When the monitor parameters are optimized, the user can wirelessly update the system for chronic event tracking. The simulated performance of the device was assessed using an in silico model with human data to predict the real-time device performance at tracking recorded seizure activity. The in silico performance was then compared against its performance in an in vitro model to capture the full environmental constraints such as sensing during stimulation at the tissue electrode interface. In vitro modeling demonstrated comparable results to the in silico model, providing verification of the software tool and model. This study provides validation evidence of the suitability of the proposed system for tracking longitudinal seizure activity. Given its flexibility, the event monitor can be adapted to track other disorders with episodic and rhythmic symptoms represented by bioelectrical behavior.Clinical relevance-An implantable neuromodulation system is presented that enables chronic tracking of physiological events in disease. This physiological monitor provides the basis for longitudinal assessments of therapy outcomes for patients, such as those with epilepsy where objective identification of patient seizure activity and rhythms might help guide therapy optimization. The system is configurable for other disease states such as Parkinson's disease and mood disorders.


Asunto(s)
Epilepsia , Humanos , Epilepsia/terapia , Prótesis e Implantes , Monitoreo Fisiológico , Procesamiento de Señales Asistido por Computador , Convulsiones/diagnóstico
2.
Exp Neurol ; 351: 113977, 2022 05.
Artículo en Inglés | MEDLINE | ID: mdl-35016994

RESUMEN

There is growing interest in using adaptive neuromodulation to provide a more personalized therapy experience that might improve patient outcomes. Current implant technology, however, can be limited in its adaptive algorithm capability. To enable exploration of adaptive algorithms with chronic implants, we designed and validated the 'Picostim DyNeuMo Mk-1' (DyNeuMo Mk-1 for short), a fully-implantable, adaptive research stimulator that titrates stimulation based on circadian rhythms (e.g. sleep, wake) and the patient's movement state (e.g. posture, activity, shock, free-fall). The design leverages off-the-shelf consumer technology that provides inertial sensing with low-power, high reliability, and relatively modest cost. The DyNeuMo Mk-1 system was designed, manufactured and verified using ISO 13485 design controls, including ISO 14971 risk management techniques to ensure patient safety, while enabling novel algorithms. The system was validated for an intended use case in movement disorders under an emergency-device authorization from the Medicines and Healthcare Products Regulatory Agency (MHRA). The algorithm configurability and expanded stimulation parameter space allows for a number of applications to be explored in both central and peripheral applications. Intended applications include adaptive stimulation for movement disorders, synchronizing stimulation with circadian patterns, and reacting to transient inertial events such as posture changes, general activity, and walking. With appropriate design controls in place, first-in-human research trials are now being prepared to explore the utility of automated motion-adaptive algorithms.


Asunto(s)
Encéfalo , Trastornos del Movimiento , Algoritmos , Encéfalo/fisiología , Cronoterapia , Humanos , Reproducibilidad de los Resultados
3.
Conf Proc IEEE Int Conf Syst Man Cybern ; 2020: 3433-3440, 2020 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-33692611

RESUMEN

Deep brain stimulation (DBS) for Parkinson's disease, essential tremor and epilepsy is an established palliative treatment. DBS uses electrical neuromodulation to suppress symptoms. Most current systems provide a continuous pattern of fixed stimulation, with clinical follow-ups to refine settings constrained to normal office hours. An issue with this management strategy is that the impact of stimulation on circadian, i.e. sleep-wake, rhythms is not fully considered; either in the device design or in the clinical follow-up. Since devices can be implanted in brain targets that couple into the reticular activating network, impact on wakefulness and sleep can be significant. This issue will likely grow as new targets are explored, with the potential to create entraining signals that are uncoupled from environmental influences. To address this issue, we have designed a new brain-machine-interface for DBS that combines a slow-adaptive circadian-based stimulation pattern with a fast-acting pathway for responsive stimulation, demonstrated here for seizure management. In preparation for first-in-human research trials to explore the utility of multi-timescale automated adaptive algorithms, design and prototyping was carried out in line with ISO risk management standards, ensuring patient safety. The ultimate aim is to account for chronobiology within the algorithms embedded in brain-machine-interfaces and in neuromodulation technology more broadly.

4.
Curr Hypertens Rep ; 16(11): 493, 2014 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-25236853

RESUMEN

Hypertension is a leading risk factor for the development of several cardiovascular diseases. As the global prevalence of hypertension increases, so too has the recognition of resistant hypertension. Whilst figures vary, the proportion of hypertensive patients that are resistant to multiple drug therapies have been reported to be as high as 16.4 %. Resistant hypertension is typically associated with elevated sympathetic activity and abnormal homeostatic reflex control and is termed neurogenic hypertension because of its presumed central autonomic nervous system origin. This resistance to conventional pharmacological treatment has stimulated a plethora of medical devices to be investigated for use in hypertension, with varying degrees of success. In this review, we discuss a new therapy for drug-resistant hypertension, deep brain stimulation. The utility of deep brain stimulation in resistant hypertension was first discovered in patients with concurrent neuropathic pain, where it lowered blood pressure and improved baroreflex sensitivity. The most promising central target for stimulation is the ventrolateral periaqueductal gray, which has been well characterised in animal studies as a control centre for autonomic outflow. In this review, we will discuss the promise and potential mechanisms of deep brain stimulation in the treatment of severe, resistant hypertension.


Asunto(s)
Sistema Nervioso Autónomo/fisiopatología , Estimulación Encefálica Profunda , Hipertensión/terapia , Sistema Nervioso Simpático/fisiopatología , Animales , Presión Sanguínea , Humanos , Hipertensión/fisiopatología
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