Detection of Wandering Behaviors Using a Body-Worn Inertial Sensor in Patients With Cognitive Impairment: A Feasibility Study

Patients with Alzheimer's disease (AD) and AD related dementias (ADRD) often experience spatial disorientation that can lead to wandering behavior, characterized by aimless or purposeless movement. Wandering behavior has been associated with falls, caregiver burden, and nursing home placement. Despite the substantial clinical consequences of wandering, there is currently no standardized approach to objectively quantify wandering behavior. In this pilot feasibility study, we used a lightweight inertial sensor to examine mobility characteristics of a small group of 12 older adults with ADRD and mild cognitive impairment in their homes. Specifically, we evaluated their compliance with wearing a sensor for a minimum of 4 days. We also examined the ability of the sensor to measure turning frequency and direction changes, given that frequent turns and direction changes during walking have been observed in patients who wander. We found that all patients were able to wear the sensor yielding quantitative turn data including number of turns over time, mean turn duration, mean peak turn speed, and mean turn angle. We found that wanderers make more frequent, quicker turns compared to non-wanderers, which is consistent with pacing or lapping behavior. This study provides preliminary evidence that continuous monitoring in patients with dementia is feasible using a wearable sensor. More studies are needed to explore if objective measures of turning behaviors collected using inertial sensors can be used to identify wandering behavior.

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The Effect of Mindfulness-Based Stress Reduction (MBSR) on Depression, Cognition, and Immunity in Mild Cognitive Impairment: A Pilot Feasibility Study

Clinical Interventions in Aging ◽

10.2147/cia.s249196 ◽

2020 ◽

Vol Volume 15 ◽

pp. 1365-1381 ◽

Cited By ~ 1

Author(s):

Rafał Marciniak ◽

Rastislav Šumec ◽

Martin Vyhnálek ◽

Kamila Bendíčková ◽

Petra Lázničková ◽

...

Keyword(s):

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Feasibility Study ◽

Stress Reduction ◽

Mindfulness Based Stress Reduction ◽

Pilot Feasibility Study

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A Preliminary Framework and Feasibility Study for Spacecraft Disturbance Source Detection and Isolation with Distributed Inertial Sensors

AIAA Scitech 2021 Forum ◽

10.2514/6.2021-1867 ◽

2021 ◽

Author(s):

Adam Augustyniak ◽

David J. Hanley ◽

Timothy W. Bretl ◽

Neil J. Hejmanowski ◽

David L. Carroll

Keyword(s):

Feasibility Study ◽

Inertial Sensors ◽

Source Detection ◽

Disturbance Source

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Reference in-vitro dataset for inertial-sensor-to-bone alignment applied to the tibiofemoral joint

Scientific Data ◽

10.1038/s41597-021-00995-8 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Ive Weygers ◽

Manon Kok ◽

Thomas Seel ◽

Darshan Shah ◽

Orçun Taylan ◽

...

Keyword(s):

Inertial Sensors ◽

Inertial Sensor ◽

Ground Truth ◽

Transformation Matrices ◽

True Model ◽

Advance Research ◽

Manual Palpation ◽

Visualization Tools ◽

Inertial Measurements

AbstractSkin-attached inertial sensors are increasingly used for kinematic analysis. However, their ability to measure outside-lab can only be exploited after correctly aligning the sensor axes with the underlying anatomical axes. Emerging model-based inertial-sensor-to-bone alignment methods relate inertial measurements with a model of the joint to overcome calibration movements and sensor placement assumptions. It is unclear how good such alignment methods can identify the anatomical axes. Any misalignment results in kinematic cross-talk errors, which makes model validation and the interpretation of the resulting kinematics measurements challenging. This study provides an anatomically correct ground-truth reference dataset from dynamic motions on a cadaver. In contrast with existing references, this enables a true model evaluation that overcomes influences from soft-tissue artifacts, orientation and manual palpation errors. This dataset comprises extensive dynamic movements that are recorded with multimodal measurements including trajectories of optical and virtual (via computed tomography) anatomical markers, reference kinematics, inertial measurements, transformation matrices and visualization tools. The dataset can be used either as a ground-truth reference or to advance research in inertial-sensor-to-bone-alignment.

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Smartphone-Based Inertial Odometry for Blind Walkers

Sensors ◽

10.3390/s21124033 ◽

2021 ◽

Vol 21 (12) ◽

pp. 4033

Author(s):

Peng Ren ◽

Fatemeh Elyasi ◽

Roberto Manduchi

Keyword(s):

Particle Filtering ◽

Inertial Sensors ◽

State Of The Art ◽

Inertial Sensor ◽

Mean Shift ◽

Gait Pattern ◽

Comparative Assessment ◽

Pedestrian Tracking ◽

Step Counter ◽

Assisted Navigation

Pedestrian tracking systems implemented in regular smartphones may provide a convenient mechanism for wayfinding and backtracking for people who are blind. However, virtually all existing studies only considered sighted participants, whose gait pattern may be different from that of blind walkers using a long cane or a dog guide. In this contribution, we present a comparative assessment of several algorithms using inertial sensors for pedestrian tracking, as applied to data from WeAllWalk, the only published inertial sensor dataset collected indoors from blind walkers. We consider two situations of interest. In the first situation, a map of the building is not available, in which case we assume that users walk in a network of corridors intersecting at 45° or 90°. We propose a new two-stage turn detector that, combined with an LSTM-based step counter, can robustly reconstruct the path traversed. We compare this with RoNIN, a state-of-the-art algorithm based on deep learning. In the second situation, a map is available, which provides a strong prior on the possible trajectories. For these situations, we experiment with particle filtering, with an additional clustering stage based on mean shift. Our results highlight the importance of training and testing inertial odometry systems for assisted navigation with data from blind walkers.

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A pilot feasibility study of an unguided, internet‐delivered cognitive behavioral therapy program for irritable bowel syndrome

Neurogastroenterology & Motility ◽

10.1111/nmo.14108 ◽

2021 ◽

Author(s):

Jocelynn T. Owusu ◽

Alice Sibelli ◽

Rona Moss‐Morris ◽

Miranda A.L. Tilburg ◽

Rona L. Levy ◽

...

Keyword(s):

Irritable Bowel Syndrome ◽

Cognitive Behavioral Therapy ◽

Feasibility Study ◽

Behavioral Therapy ◽

Cognitive Behavioral ◽

Therapy Program ◽

Irritable Bowel ◽

Pilot Feasibility Study

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Inertial Sensor Reliability and Validity for Static and Dynamic Balance in Healthy Adults: A Systematic Review

Sensors ◽

10.3390/s21155167 ◽

2021 ◽

Vol 21 (15) ◽

pp. 5167

Author(s):

Nicky Baker ◽

Claire Gough ◽

Susan J. Gordon

Keyword(s):

Systematic Review ◽

Discriminant Validity ◽

Inertial Sensors ◽

Postural Sway ◽

Inertial Sensor ◽

Dynamic Balance ◽

Healthy Adults ◽

Gait Velocity ◽

Time Data ◽

Targeted Interventions

Compared to laboratory equipment inertial sensors are inexpensive and portable, permitting the measurement of postural sway and balance to be conducted in any setting. This systematic review investigated the inter-sensor and test-retest reliability, and concurrent and discriminant validity to measure static and dynamic balance in healthy adults. Medline, PubMed, Embase, Scopus, CINAHL, and Web of Science were searched to January 2021. Nineteen studies met the inclusion criteria. Meta-analysis was possible for reliability studies only and it was found that inertial sensors are reliable to measure static standing eyes open. A synthesis of the included studies shows moderate to good reliability for dynamic balance. Concurrent validity is moderate for both static and dynamic balance. Sensors discriminate old from young adults by amplitude of mediolateral sway, gait velocity, step length, and turn speed. Fallers are discriminated from non-fallers by sensor measures during walking, stepping, and sit to stand. The accuracy of discrimination is unable to be determined conclusively. Using inertial sensors to measure postural sway in healthy adults provides real-time data collected in the natural environment and enables discrimination between fallers and non-fallers. The ability of inertial sensors to identify differences in postural sway components related to altered performance in clinical tests can inform targeted interventions for the prevention of falls and near falls.

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