System and Method for the Inference of Activities of Daily Living and Instrumental Activities of Daily Living Automatically

• US 20150080767A1
• Filed: 11/24/2014
• Published: 03/19/2015
• Est. Priority Date: 03/10/2004
• Status: Active Grant

• Current Assignee: The University of Virginia Licensing and Ventures Group
• Original Assignee: The University of Virginia Licensing and Ventures Group
• Inventors: Alwan, Majd, Felder, Robin A., Kell, Steven W., Wood, Sarah G., Cvetanovich, Michael, Turner, Beverly L., Holman, J. William
• Granted Patent: US 9,968,283 B2
• Time in Patent Office: Days
• US Class Current: 600/595
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2562/0247 Pressure sensors
• CPC Class Codes: A61B 2562/046 in a matrix array
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/1112 Global tracking of patients, e.g. by using GPS
• CPC Class Codes: A61B 5/1113 Local tracking of patients, e.g. in a hospital or private home
• CPC Class Codes: A61B 5/1115 Monitoring leaving of a patient support, e.g. a bed or a wheelchair
• CPC Class Codes: A61B 5/1116 Determining posture transitions
• CPC Class Codes: A61B 5/202 Assessing bladder functions, e.g. incontinence assessment
• CPC Class Codes: A61B 5/6887 mounted on external non-worn devices, e.g. non-medical devices
• CPC Class Codes: A61B 5/6889 Rooms
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence

Abstract

A method and related system to, among other things, automatically infer answers to all of the ADL questions and the first four questions of the IADL in the home. The inference methods detect the relevant activities unobtrusively, continuously, accurately, objectively, quantifiably and without relying on the patient'"'"'s own memory (which may be fading due to aging or an existing health condition, such as Traumatic Brain Injury (TBI)) or on a caregiver'"'"'s subjective report. The methods rely on the judicious placement of a number of sensors in the subject'"'"'s place of residence, including motion detection sensors in every room, the decomposition of each relevant activity into the sub-tasks involved, identification of additional sensors required to detect the relevant sub-tasks and spatial-temporal conditions between the signals of sensors to formulate the rules that will detect the occurrence of the specific activities of interest.

Claims

1. A method to automatically derive answers to the questions of two clinical functional assessment instruments activities of daily living (ADLs), and all but one of the instrumental activities of daily living (IADLs) relying on sensors targeting the side-effects of the activities, said method comprising:

date and time stamping sensor firings; and

setting a set of rules method where the spatio-temporal relationships of sensor firings are examined and analyzed to infer the occurrence of activities of interest, wherein said rules include at least one of the following;

a rule to automatically bathing/showering,

a rule to automatically detect dressing,

a rule to automatically detect toileting events,

a rule to automatically detect the ability to ambulate (get out of bed/chair),

a rule to automatically detect problems in controlling bladder and/or bowels,

a rule to automatically detect the ability to feed oneself,

a rule to automatically detect the ability to get to places outside of walking distance,

a rule to automatically detect the ability to shop for groceries,

a rule to automatically detect the ability to prepare meals, and

a rule to automatically detect the ability to do house work.

2. A system to automatically derive answers to the questions of two clinical functional assessment instruments activities of daily living (ADLs), and all but one of the instrumental activities of daily living (IADLs), said system comprising:

a sensor module, wherein said sensor module targets the side-effects of the activities; and

a processor module, said processor module programmed to;

a) date and time stamp sensor firings; and

b) set a set of rules where the spatio-temporal relationships of sensor firings are examined and analyzed to infer the occurrence of activities of interest,

wherein said rules include at least one of the following;

a rule to automatically bathing/showering,

a rule to automatically detect dressing,

a rule to automatically detect toileting events,

a rule to automatically detect the ability to ambulate (get out of bed/chair),

a rule to automatically detect problems in controlling bladder and/or bowels,

a rule to automatically detect the ability to feed oneself,

a rule to automatically detect the ability to get to places outside of walking distance,

a rule to automatically detect the ability to shop for groceries,

a rule to automatically detect the ability to prepare meals, and

a rule to automatically detect the ability to do house work.

3. A computer program product comprising computer useable medium having computer program logic for enabling at least one processor in a computer system to automatically derive answers to the questions of two clinical functional assessment instruments activities of daily living (ADLs), and all but one of the instrumental activities of daily living (IADLs) relying on sensors targeting the side-effects of the activities, said computer logic comprising:

date and time stamping sensor firings; and

setting a set of rules method where the spatio-temporal relationships of sensor firings are examined and analyzed to infer the occurrence of activities of interest, wherein said rules include at least one of the following;

a rule to automatically bathing/showering,

a rule to automatically detect dressing,

a rule to automatically detect toileting events,

a rule to automatically detect the ability to ambulate (get out of bed/chair),

a rule to automatically detect problems in controlling bladder and/or bowels,

a rule to automatically detect the ability to feed oneself,

a rule to automatically detect the ability to get to places outside of walking distance,

a rule to automatically detect the ability to shop for groceries,

a rule to automatically detect the ability to prepare meals, and

a rule to automatically detect the ability to do house work.