Finger tapping and pre-attentive sensorimotor timing in adults with ADHD.

Sensorimotor timing deficits are considered central to attention-deficit/hyperactivity disorder (ADHD). However, the tasks establishing timing impairments often involve interconnected processes, including low-level sensorimotor timing and higher level executive processes such as attention. Thus, the source of timing deficits in ADHD remains unclear. Low-level sensorimotor timing can be isolated from higher level processes in a finger-tapping task that examines the motor response to unexpected shifts of metronome onsets. In this study, adults with ADHD and ADHD-like symptoms (n = 25) and controls (n = 26) performed two finger-tapping tasks. The first assessed tapping variability in a standard tapping task (metronome-paced and unpaced). In the other task, participants tapped along with a metronome that contained unexpected shifts (±15, 50 ms); the timing adjustment on the tap following the shift captures pre-attentive sensorimotor timing (i.e., phase correction) and thus should be free of potential higher order confounds (e.g., attention). In the standard tapping task, as expected, the ADHD group had higher timing variability in both paced and unpaced tappings. However, in the pre-attentive task, performance did not differ between the ADHD and control groups. Together, results suggest that low-level sensorimotor timing and phase correction are largely preserved in ADHD and that some timing impairments observed in ADHD may stem from higher level factors (such as sustained attention).

Reliability of Sleep Measures from Four Personal Health Monitoring Devices Compared to Research-Based Actigraphy and Polysomnography.

Polysomnography (PSG) is the "gold standard" for monitoring sleep. Alternatives to PSG are of interest for clinical, research, and personal use. Wrist-worn actigraph devices have been utilized in research settings for measures of sleep for over two decades. Whether sleep measures from commercially available devices are similarly valid is unknown. We sought to determine the validity of five wearable devices: Basis Health Tracker, Misfit Shine, Fitbit Flex, Withings Pulse O2, and a research-based actigraph, Actiwatch Spectrum. We used Wilcoxon Signed Rank tests to assess differences between devices relative to PSG and correlational analysis to assess the strength of the relationship. Data loss was greatest for Fitbit and Misfit. For all devices, we found no difference and strong correlation of total sleep time with PSG. Sleep efficiency differed from PSG for Withings, Misfit, Fitbit, and Basis, while Actiwatch mean values did not differ from that of PSG. Only mean values of sleep efficiency (time asleep/time in bed) from Actiwatch correlated with PSG, yet this correlation was weak. Light sleep time differed from PSG (nREM1 + nREM2) for all devices. Measures of Deep sleep time did not differ from PSG (SWS + REM) for Basis. These results reveal the current strengths and limitations in sleep estimates produced by personal health monitoring devices and point to a need for future development.