Demographic details for the ten participants that carried out each specificity activity.

<p>Demographic details for the ten participants that carried out each specificity activity.</p

Specificity of each activity monitor during the passive non-stepping activities.

<p>Data for deskwork, taking an elevator and automobile driving on a motorway have been excluded due to the high number of zero false positives correctly recorded by the devices during these activities. The mean false positives detected during the bus journey are expressed as false positives detected per minute as represented by the left y-axis. The mean false positives detected during the driving activity are expressed as false positives detected per kilometer driven as represented by the right y-axis. * P ≤ 0.001 vs. zero false positives, # P < 0.05 vs. zero false positives. N = 10/activity. Data represents mean ± SEM.</p

Estimated false positives generated daily based on conservative estimates of time spent on sample activities for different categories of potential activity monitor users over a typical 12-hour day.

<p>Estimated false positives generated daily based on conservative estimates of time spent on sample activities for different categories of potential activity monitor users over a typical 12-hour day.</p

Specificity (fp/min) of each activity monitor during the moderate non-stepping activities.

<p>While the ActivPAL^™ registered a number of fp/min during the functional reaching task, this was found to be non-significant. *** P < 0.001 vs. video recording (zero fp/min), ** P < 0.01 vs. video recording (zero fp/min). N = 10/activity. Data represents mean ± SEM.</p

Specificity (fp/min) of each activity monitor during the active non-stepping activities.

<p>*** P < 0.001 vs. video recording (zero fp/min), * P < 0.05 vs. video recording (zero fp/min). N = 10/activity. Data represents mean ± SEM.</p

Mean false positives per minute for all activity monitors during the non-stepping prescribed activities.

<p>Mean false positives per minute for all activity monitors during the non-stepping prescribed activities.</p

Positioning of each activity monitor.

<p>The ActivPAL^™ is worn on the right thigh, the NL-2000^™ on the left hip, the Withings^™ on the right hip, the Jawbone^™ on the right wrist and the Fitbit^™ at the level of the chest.</p

Double-tap interaction as an actuation mechanism for on-demand cueing in parkinson’s disease

Freezing of Gait (FoG) is one of the most debilitating symptoms of Parkinson’s disease and is an important contributor to falls. When the management of freezing episodes cannot be achieved through medication or surgery, non-pharmacological methods, such as cueing, have emerged as effective techniques, which ameliorates FoG. The use of On-Demand cueing systems (systems that only provide cueing stimuli during a FoG episode) has received attention in recent years. For such systems, the most common method of triggering the onset of cueing stimuli, utilize autonomous real-time FoG detection algorithms. In this article, we assessed the potential of a simple double-tap gesture interaction to trigger the onset of cueing stimuli. The intended purpose of our study was to validate the use of double-tap gesture interaction to facilitate Self-activated On-Demand cueing. We present analyses that assess if PwP can perform a double-tap gesture, if the gesture can be detected using an accelerometer’s embedded gestural interaction recognition function and if the action of performing the gesture aggravates FoG episodes. Our results demonstrate that a double-tap gesture may provide an effective actuation method for triggering On-Demand cueing. This opens up the potential future development of self-activated cueing devices as a method of On-Demand cueing for PwP and others

Comparison of overall frequency of error in the measurement of lap times for both Finis Swimsense and Garmin Swim.

<p>Comparison of overall frequency of error in the measurement of lap times for both Finis Swimsense and Garmin Swim.</p

Comparison of results for stroke rate, stroke length and average speed.

<p>Mean score, standard deviation (SD), standard error of the mean (SE), 95% confidence intervals, interclass correlation coefficient (ICC), mean absolute percentage error (MAPE) and the error range are presented for both Finis <i>Swimsense</i> and Garmin <i>Swim</i> monitors, where applicable and compared with the criterion measures extracted from video footage.</p