Detection of gait and postures using a miniaturised triaxial accelerometer-based system: Accuracy in community-dwelling older adults

Posture and Movement Classification: The Comparison of Tri-Axial Accelerometer Numbers and Anatomical Placement

“…Median sensitivities and PPVs for jogging were slightly lower at 93% and 98% for the single ankle accelerometer than the other combinations and placements due to the correlation of increasing amplitude variation with increasing movement resulting in some jogging seconds being misclassified as walking and vice versa. However, despite some accelerometer locations producing more accurate results than others, all tested accelerometer combinations and placements in this study detected walking/ fidgeting with moderate to high accuracy (median sensitivities and PPVs from 76% to 95%) and jogging with high accuracy (median sensitivities and PPVs from 93% to 100%; (Table 3)) which were comparable to other studies [12,16]. While both thigh-ankle and waist-thigh accelerometers produced results of high accuracy for walking and jogging detection, the thigh-ankle accelerometers had higher sensitivity values than the waist-thigh accelerometers and only slightly lower PPVs (Table 2) consistent with a previous study on level walking, stair ascent, and descent detection [25].…”

“…[27], however, the results were still comparable to those from other studies involving two accelerometer locations [12] and could still provide beneficial information in the event of waist accelerometer failure or if it is not feasible for a patient to wear a waist accelerometer. While some studies have investigated posture identification using only one accelerometer on the waist [ 15,17] or lower back [16], the protocols used to test the algorithms validities did not include fidgeting of the feet during standing or sitting postures which could possibly reduce the accuracy. Furthermore, difficulties in differentiating between standing and sitting using an accelerometer located on the waist have been reported [8].…”

“…For more complex movement classification systems, higher numbers of activity monitors (up to 36) have been used [9,10]. Many different studies have demonstrated postural orientation and movement identification using varying numbers of activity monitors (from 1 to 7) and different locations [6,[11][12][13][14][15][16][17][18][19][20][21][22][23][24]. However, only a few studies have investigated how the robustness of any of these postural and movement identification algorithms would change with different activity monitor numbers and locations [5,25,26].…”

Identifying Types of Physical Activity With a Single Accelerometer: Evaluating Laboratory-trained Algorithms in Daily Life

“…2). However, classifying this activity category was already problematic in the laboratory dataset and difficulties with a similar category in a home environment have previously been reported [35]. Lastly, identification of cycling was overly sensitive: the variety of dynamic motions not present in the laboratory data seems to have created a decision boundary which in daily life includes many dynamic activities.…”

Physical activity, muscle strength, and exercise capacity 3 months after severe sepsis and septic shock

“…The patient's PADL was determined by monitoring movements with an accelerometer (Dynaport Minimod, McRoberts, Netherlands) that was developed and validated in patients with chronic obstructive pulmonary disease (COPD) [32] and other populations [33,34]. This small (54 9 84 9 8.5 mm) and light (45 g) high-resolution triaxial sensor quantifies the time spent performing various activities, such as sitting, lying, standing, and walking, and changes in body position and energy expenditure.…”