scholarly journals Reactive stepping behaviour in response to forward loss of balance predicts future falls in community-dwelling older adults

2014 ◽  
Vol 44 (1) ◽  
pp. 109-115 ◽  
Author(s):  
Christopher P. Carty ◽  
Neil J. Cronin ◽  
Deanne Nicholson ◽  
Glen A. Lichtwark ◽  
Peter M. Mills ◽  
...  
Keyword(s):  
Older Adults ◽  
Community Dwelling ◽  
Loss Of Balance ◽  
Community Dwelling Older Adults ◽  
Reactive Stepping

scholarly journals Automated Loss-of-Balance Event Identification in Older Adults at Risk of Falls during Real-World Walking Using Wearable Inertial Measurement Units

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4661
Author(s):  
Jeremiah Hauth ◽  
Safa Jabri ◽  
Fahad Kamran ◽  
Eyoel W. Feleke ◽  
Kaleab Nigusie ◽  
...  
Keyword(s):  
Older Adults ◽  
Real World ◽  
Characteristic Curve ◽  
Community Dwelling ◽  
Recording Device ◽  
Learning Approaches ◽  
Discriminative Ability ◽  
Inertial Measurement ◽  
Loss Of Balance ◽  
Community Dwelling Older Adults

Loss-of-balance (LOB) events, such as trips and slips, are frequent among community-dwelling older adults and are an indicator of increased fall risk. In a preliminary study, eight community-dwelling older adults with a history of falls were asked to perform everyday tasks in the real world while donning a set of three inertial measurement sensors (IMUs) and report LOB events via a voice-recording device. Over 290 h of real-world kinematic data were collected and used to build and evaluate classification models to detect the occurrence of LOB events. Spatiotemporal gait metrics were calculated, and time stamps for when LOB events occurred were identified. Using these data and machine learning approaches, we built classifiers to detect LOB events. Through a leave-one-participant-out validation scheme, performance was assessed in terms of the area under the receiver operating characteristic curve (AUROC) and the area under the precision recall curve (AUPR). The best model achieved an AUROC ≥0.87 for every held-out participant and an AUPR 4-20 times the incidence rate of LOB events. Such models could be used to filter large datasets prior to manual classification by a trained healthcare provider. In this context, the models filtered out at least 65.7% of the data, while detecting ≥87.0% of events on average. Based on the demonstrated discriminative ability to separate LOBs and normal walking segments, such models could be applied retrospectively to track the occurrence of LOBs over an extended period of time.

scholarly journals Which Are the Key Kinematic and Kinetic Components to Distinguish Recovery Strategies for Overground Slips Among Community-Dwelling Older Adults?

2020 ◽  
Vol 36 (4) ◽  
pp. 217-227
Author(s):  
Shuaijie Wang ◽  
Yiru Wang ◽  
Yi-Chung (Clive) Pai ◽  
Edward Wang ◽  
Tanvi Bhatt
Keyword(s):  
Older Adults ◽  
Sagittal Plane ◽  
Community Dwelling ◽  
Forward Dynamics ◽  
Plantar Flexor ◽  
Factors Affecting ◽  
Recovery Strategies ◽  
Loss Of Balance ◽  
Community Dwelling Older Adults ◽  
Do So

Slip outcomes are categorized as either a backward loss of balance (LOB) or a no loss of balance (no-LOB) in which an individual does not take a backward step to regain their stability. LOB includes falls and nonfalls, while no-LOB includes skate overs and walkovers. Researchers are uncertain about which factors determine slip outcomes and at which critical instants they do so. The purpose of the study was to investigate factors affecting slip outcomes in proactive and early reactive phases by analyzing 136 slip trials from 68 participants (age: 72.2 [5.3] y, female: 22). Segment angles and average joint moments in the sagittal plane of the slipping limb were compared for different slip outcomes. The results showed that knee flexor, hip extensor, and plantar flexor moments were significantly larger for no-LOB than for LOB in the midproactive phase, leading to smaller shank-ground and foot-ground angles at the slip onset, based on forward dynamics. In the early reactive phase, the hip extensor and plantar flexor moments were larger for no-LOB than for LOB, and all segment angles were smaller for no-LOB. Our findings indicate that the shank angle and knee moment were the major determinants of slip outcomes in both proactive and reactive phases.

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