Publications

Patients with spinal cord injury (SCI) have an increased risk of sleep-disordered breathing (SDB), which can lead to serious comorbidities and impact patients’ recovery and quality of life. However, sleep tests are rarely performed on SCI patients, given their multiple health needs and the cost and complexity of diagnostic equipment. The objective of this study was to use a novel smartphone system as a simple non-invasive tool to monitor SDB in SCI patients. We recorded pulse oximetry, acoustic, and accelerometer data using a smartphone during overnight tests in 19 SCI patients and 19 able-bodied controls. Then, we analyzed these signals with automatic algorithms to detect desaturation, apnea, and hypopnea events and monitor sleep position. The apnea–hypopnea index (AHI) was significantly higher in SCI patients than controls (25 ± 15 vs. 9 ± 7, p < 0.001). We found that 63% of SCI patients had moderate-to-severe SDB (AHI ? 15) in contrast to 21% of control subjects. Most SCI patients slept predominantly in supine position, but an increased occurrence of events in supine position was only observed for eight patients. This study highlights the problem of SDB in SCI and provides simple cost-effective sleep monitoring tools to facilitate the detection, understanding, and management of SDB in SCI patients.

JTD Keywords: apnea syndrome, biomedical signal processing, individuals, mhealth, monitoring, nasal resistance, people, position, prevalence, questionnaire, sample, sleep apnea, sleep position, sleep-disordered breathing, smartphone, time, Apnea-hypopnea indices, Biomedical signal processing, Biomedical signals processing, Cost effectiveness, Diagnosis, Mhealth, Monitoring, Noninvasive medical procedures, Oximeters, Oxygen-saturation, Patient rehabilitation, Simple++, Sleep apnea, Sleep position, Sleep research, Sleep-disordered breathing, Smart phones, Smartphone, Smartphones, Spinal cord injury, Spinal cord injury patients

Robot-assisted rehabilitation therapies usually focus on physical aspects rather than on cognitive factors. However, cognitive aspects such as attention, motivation, and engagement play a critical role in motor learning and thus influence the long-term success of rehabilitation programs. This paper studies motor-related EEG activity during the execution of robot-assisted passive movements of the upper limb, while participants either: i) focused attention exclusively on the task; or ii) simultaneously performed another task. Six healthy subjects participated in the study and results showed lower desynchronization during passive movements with another task simultaneously being carried out (compared to passive movements with exclusive attention on the task). In addition, it was proved the feasibility to distinguish between the two conditions.

JTD Keywords: Electrodes, Electroencephalography, Induction motors, Medical treatment, Robot sensing systems, Time frequency analysis, Biomechanics, Cognition, Electroencephalography, Medical robotics, Medical signal detection, Medical signal processing, Patient rehabilitation, Attention, Cognitive aspects, Desynchronization, Engagement, Motivation, Motor learning, Motor task, Motor-related EEG activity, Physical aspects, Robot-assisted passive movement detection, Robot-assisted rehabilitation therapies, Upper limb

The design of mechanical joints that kinematically behave as their biological counterparts is a challenge that if not addressed properly can cause inadequate forces transmission between robot and patient. This paper studies the interaction forces in rehabilitation therapies of the elbow joint. To measure the effect of orthosis-patient misalignments, a force sensor with a novel distributed architecture has been designed and used for this study. A test-bed based on an industrial robot acting as a virtual exoskeleton that emulates the action of a therapist has been developed and the interaction forces analyzed.

JTD Keywords: Force, Force measurement, Force sensors, Joints, Medical treatment, Robot sensing systems, Force sensors, Medical robotics, Patient rehabilitation, Biological counterparts, Distributed architecture, Elbow joint, Force sensor, Inadequate forces transmission, Industrial robot, Mechanical joints design, Orthosis-patient misalignments, Patient-orthosis interaction forces, Rehabilitation therapies, Robot, Test-bed, Virtual exoskeleton