Background. Transcranial direct current stimulation (tDCS) of the primary motor cortex (M1) has an analgesic effect superior to a placebo in chronic pain. Some years ago, tDCS was implemented at the Hospital Nacional of Paraplegics (Toledo, Spain) to treat patients with pharmacological resistance to chronic pain. Objective. The main objectives of this study with tDCS were (1) to confirm the safety of one-year treatment; (2) to estimate the number of patients after one year in treatment; (3) to describe the effects of tDCS on the pain intensity during one-year treatment; and (4) to identify factors related to treatment success. Methods. This was a retrospective study conducted at the National Hospital for Paraplegics with 155 patients with pharmacologically resistant chronic pain. Anodal tDCS was applied over the M1 for 20 min at 1.5 mA for 10 treatment sessions from Monday to Friday (Induction phase), followed by 2-3 sessions per month (Maintenance phase). Pain intensity was assessed using a Visual Analogue Scale (VAS). Results. Anodal tDCS on M1 confirmed the reduction in the pain intensity. Moreover, 58% of outpatients completed one year of treatment. Only the VAS values obtained during the baseline influenced the response to treatment. Patients with a very high VAS at the baseline were more likely to not respond adequately to tDCS treatment. Conclusions. Anodal tDCS over M1 is an adequate therapy (safe and efficient) to treat drug-resistant chronic pain. Moreover, pain intensity at the start of treatment could be a predictor of patients' continuity with tDCS for at least one year.

Neuropathic pain is a difficult condition to treat and would require reliable biomarkers to personalise and optimise treatments. To date, pain levels are mostly measured with subjective scales, but research has shown that electroencephalography (EEG) and heart rate variability (HRV) can be linked to those levels. Internet of Things technology could allow embedding EEG and HRV in easy-to-use systems that patients can use at home in their daily life. We have developed a system for home monitoring that includes a portable EEG device, a tablet application to guide patients through imaginary motor tasks while recording EEG, a wearable HRV sensor and a mobile phone app to report pain levels. We are using this system in a clinical study involving 15 spinal cord injury patients for one month. Preliminary results show that relevant data are being collected, with inter and intra-patients variability for both HRV and pain levels, and that the mobile phone app is perceived as usable, of good quality and useful. However, because of its complexity, the system requires some effort from patients, is sometimes unreliable and the collected EEG signals are not always of the desired quality.

Internet of Things (IoT) can work as a useful tool for clinical research. We developed a software platform that allows researchers to publish clinical studies and volunteers to participate into them using an app and connected IoT devices. The platform includes a REST API, a web interface for researchers and an app that collects data during tasks volunteers are invited to contribute. Nine tasks have been developed: Forms, Positioning, Finger tapping, Pulse-oximetry, Peak Flow measurement, Activity tracking, Data query, Queen’s College step test and Six-minute walk test. These leverage sensors embedded in the phone, connected Bluetooth devices and additional APIs like HealthKit and Google Fit. Currently, the platform is used in two clinical studies by 25 patients: an asthma management study in the United Kingdom, and a neuropathic pain management study in Spain.

Focal application of transcranial static magnetic field stimulation (tSMS) over the human motor cortex induces local changes in cortical excitability. Whether tSMS can also induce distant network effects, and how these local and distant effects may vary over time, is currently unknown. In this study, we applied 10 min tSMS over the left motor cortex of healthy subjects using a real/sham parallel design. To measure tSMS effects at the sensori-motor network level, we used resting-state fMRI. Real tSMS, but not sham, reduced functional connectivity within the stimulated sensori-motor network. This effect of tSMS showed time-dependency, returning to sham levels after the first 5 min of fMRI scanning. With 10 min real tSMS over the motor cortex we did not observe effects in other functional networks examined (default mode and visual system networks). In conclusion, 10 min of tSMS over a location within the sensori-motor network reduces functional connectivity within the same functional network.