This article was downloaded by: [Case Western Reserve University]On: 04 November 2014, At: 17:26Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

Assistive Technology: The Official Journal of RESNAPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/uaty20

The Design of an Interactive Assistive Kitchen SystemMaurizio Ficocelli Ph.D a & Goldie Nejat Ph.D b ca Department of Mechanical Engineering , State University of New York , Stony Brook , NewYork , USAb Department of Mechanical and Industrial Engineering , University of Toronto , Toronto ,Ontario , Canadac Toronto Rehabilitation Institute , Toronto , Ontario , CanadaAccepted author version posted online: 13 Feb 2012.Published online: 27 Sep 2012.

To cite this article: Maurizio Ficocelli Ph.D & Goldie Nejat Ph.D (2012) The Design of an Interactive Assistive Kitchen System,Assistive Technology: The Official Journal of RESNA, 24:4, 246-258, DOI: 10.1080/10400435.2012.659834

To link to this article: http://dx.doi.org/10.1080/10400435.2012.659834

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) containedin the publications on our platform. However, Taylor & Francis, our agents, and our licensors make norepresentations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of theContent. Any opinions and views expressed in this publication are the opinions and views of the authors, andare not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon andshould be independently verified with primary sources of information. Taylor and Francis shall not be liable forany losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoeveror howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use ofthe Content.

This article may be used for research, teaching, and private study purposes. Any substantial or systematicreproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in anyform to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Assistive Technology®, 24:246–258, 2012Copyright © 2012 RESNAISSN: 1040-0435 print/1949-3614 onlineDOI: 10.1080/10400435.2012.659834

The Design of an Interactive AssistiveKitchen System

Maurizio Ficocelli, Ph.D1 andGoldie Nejat, Ph.D2,3

1Department of MechanicalEngineering, State University ofNew York at Stony Brook, StonyBrook, New York2Department of Mechanicaland Industrial Engineering,University of Toronto, Toronto,Ontario, Canada3Toronto RehabilitationInstitute, Toronto, Ontario,Canada

ABSTRACT As the world’s elderly population drastically increases,aging-related cognitive impairments have become one of the biggesthealthcare concerns. In this paper, we present the design of an assistive kitchensystem consisting of a user interface with two-way speech communication andan automated cabinet system to help promote aging-in-place. The assistivekitchen system incorporates a cognitive assistance feature that helps the userin overcoming initiation, planning, attention, and memory deficits, whileperforming kitchen-based activities of daily living (ADLs) such as storing andretrieving items, and obtaining recipes for meal preparation. This feature workssynchronously with the automated kitchen cabinet to directly provide thelocation of an item to a user, bring the item in closer reach and also promptthe user to retrieve the item. An initial prototype of the assistive kitchensystem has been developed and performance testing has been conducted.The testing has shown high success rates for users’ retrieving and storingspecified kitchen items. A small scale study was also conducted measuring theacceptance and use of the proposed system by older adults. The results showpromise for the further development and use of the system for the outlinedkitchen ADLs.

KEYWORDS assistive kitchen system, automated cabinet, item retrieval/storage

Address correspondence to GoldieNejat, Mechanical and IndustrialEngineering, 5 King’s College Road,Toronto, Ontario, M5S 3G8 Canada.E-mail: nejat@mie.utoronto.ca

INTRODUCTIONIn the next few decades, 20%–32% of the population of a number of coun-

tries such as Canada, France, Germany, Italy, Japan, and the U.S. will be overthe age of 65 (Kinsella & Velkolt, 2001; Dobriansky, Suzman, & Hodes, 2007).For this aging population, there is a high prevalence of cognitive impairment.Cognitive impairment can progressively diminish a person’s memory, orienta-tion, verbal skills, visuospatial ability, abstract reasoning, and attentional skills(Tatemichi et al., 1994), hence, increasing the need for assistance with everydayactivities. In general, this population overwhelmingly prefers to stay in theirhomes and age-in-place as independently as possible (Mahoney, Mahoney, &Liss, 2009). However, a decline in cognitive abilities may make it difficult tomaintain such independence in the comfort of their own homes.

246

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

To date, research has been conducted to providesolutions to promote aging-in-place. In order to matchthe high demand for health care services; various“Smart Home” initiatives are being developed. Theseinitiatives can broadly be divided into three differentcategories: (1) projects focused on providing a meansof telecommunication or “virtual visits” between theelderly and their relatives using remote monitoring(Mahoney, Mutchler, Tarlow, & Liss, 2008), (2) systemsthat help users with cognitive and physical impair-ments perform activities of daily living (ADLs) inde-pendently (Lesser et al., 1999; Rantz et al., 2006;Yamazaki, 2006; Mihailidis, Boger, Craig, & Hoey,2008), and (3) wearable accessories or devices that canmonitor the health of a person (Park & Jayaraman,2003; Korhonen, Parkka, & Van Gils, 2003; Asada,Shaltis, Reisner, Rhee, & Hutchinson, 2003; Tierney,Tamada, Potts, Jovanovic, & Garg, 2001).

Our research focuses on the second category ofsmart home systems, namely on the development ofassistive technologies for the elderly in order to assistthem with ADLs to promote aging-in-place (Nejat &Ficocelli, 2008; Chan, Nejat, & Chen, 2011; McColl,Chan, & Nejat, 2012). ADLs can be defined as (Lawton& Brody, 1969; Rogers, Meyer, Walker, & Fisk, 1998):(1) self-maintenance activities which include the abil-ity to eat, dress, groom, and bathe; (2) instrumentalactivities which include the ability to prepare food,do housekeeping, organize finances, buy necessitiesand manage medications; and (3) enhanced activitieswhich include participation in cognitively and sociallystimulating leisure activities.

Even though a number of smart home technolo-gies have been developed to assist the elderly withADLs around the home, few have actually focusedon what particularly happens in the kitchen envi-ronment. Our recent work focuses on the develop-ment of an assistive kitchen environment to enablethe elderly with cognitive impairments to indepen-dently carry out regular kitchen activities. Our designaims at incorporating the following two essential fea-tures of an assistive kitchen system: (1) CognitiveAssistance: which assists users in kitchen activitiessuch as remembering the locations of items andassisting step-by-step in the meal preparation process,by using voice and visual prompting interfaces, and(2) Increased Accessibility: which allows easy access toout of reach items in the kitchen through automateddevices.

In the last few decades, kitchen designs andappliances have become more automated usingmicroprocessors and an assortment of sensor andactuator technologies, however, these kitchens havestill been designed without considering the needs ofelderly users. When considering designing an assistivekitchen for the elderly there are four main requirementsthat should be considered: (1) information providing,(2) storing and retrieving of items, (3) meal prepara-tion and cooking, and (4) meal monitoring. In thispaper, we present the design and initial prototype ofan interactive assistive kitchen system for the elderlyfocusing on the following main activities: (1) informa-tion providing in terms of recalling items’ availabilityand locations, (2) storing and retrieving items from cab-inet shelves, and (3) recipe providing. A performancestudy is also presented to verify the feasibility of theproposed system and its acceptance and future use.

This paper addresses the need for an assistive kitchensystem that incorporates a cognitive assistance featureto help a user overcome initiation, planning, attention,and memory deficits, while performing the regularkitchen activities of storing and retrieving items, andrecipe finding. This feature works synchronously withan automated kitchen cabinet that enhances a user’saccessibility in physically finding, retrieving and stor-ing kitchen items. Our intended user population forthe assistive kitchen system will range from individualshaving mild to moderate cognitive decline as definedby the Global Deterioration Scale (Reisberg, Ferris, deLeon, & Crook, 1982).

To date, only a handful of other assistive tech-nologies have been developed to assist individuals inkitchen environments. These technologies can be cate-gorized as either providing cognitive assistance or phys-ical assistance. With respect to aids that can be utilizedin the kitchen for people with cognitive impairments,PDAs and touch screens providing step-by-step mealpreparation instructions have been a popular approachsuch as the Visual Assistant (2011). However, these sys-tems do not use natural communication modes thatelderly individuals are familiar with and require thatthe items needed for meal preparation be found inthe kitchen solely by the user. This latter task canbe particularly difficult for someone with cognitiveimpairment as there are a number of cabinets and draw-ers in the kitchen. Other systems designed for memoryaids also include the Cook’s Collage visual display sys-tem (Tran, Calcaterra, & Mynatt, 2005), and Archipel

247 Design of an Interactive Assistive Kitchen System

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

touch screen system (Giroux, Bauchet, Pigot, Lussier-Desrochers, & Lachappelle, 2008). The Cook’s Collagedisplay system provides to the user a visual summaryof ongoing kitchen activities taking place on a coun-tertop, as recorded from two webcams, to remind theuser of actions he/she has already performed such aswhich ingredients were already added and the countfor each ingredient used. The Archipel system providesinstructions to a user to complete a predefined taskchosen by the user by interfacing to devices placedin the environment that use lights or sounds to drawthe attention of the user to a particular location inthe kitchen. Robot assistants are currently also beingdeveloped to undertake such tasks in the future suchas setting the table, cooking and washing the dishes(Beetz et al., 2008; Asfour et al., 2006). However, it willbe several years before these robotic systems are readilyavailable as well as cost-effective enough to be placed inthe homes of elderly individuals. In addition, a numberof safety concerns also still need to be considered withthis technology as the robots will be performing thesetasks autonomously in human occupied environments.

Currently, two popular accessible automated cabi-net designs are available for kitchens known as theDIAGO 504 Adjustable Height Cabinet (2010) andthe VERTI Adjustable Height Shelving (2010). TheDIAGO 504 system automatically moves an entirecabinet unit down over counter space for a user toreach items whereas the VERTI system simultaneouslylowers all the shelves in a cabinet through the openbottom of the cabinet. These systems can be con-trolled by a remote control, or a push button placedeither beside the cabinets or on the wall. The maintarget consumer for these products are people withlimited mobility in their lower body. The PersonalMobility and Manipulation Appliance (Grindle, Wang,Salatin, Vazquez, & Cooper, 2011) has been designedfor individuals with both lower and upper limb dis-abilities. The system consists of two robotic arms thatare mounted on a mobile robotic base. Preliminarytests have been conducted with this system for taskssuch as opening a refrigerator, retrieving and opening acontainer and then putting it in the microwave.

Our proposed interactive kitchen system focuseson providing cognitive assistance as well as increasedaccessibility to elderly individuals in order to encour-age as well as aid these individuals in performinginstrumental ADLs. In particular, the system providesan interactive environment to find and retrieve items

of interest and recipes in order to prepare meals viaa unique user interface and automated cabinet sys-tem. The automated cabinet has been designed withthe ability to only lower a single shelf at a timewithin the original fixed frame of a cabinet. This is animportant unique design feature as the system directlyprovides the location of an item to a user, brings theitem in closer reach and also prompts the user toretrieve the item. Our aim in developing the assistivekitchen system is to provide elderly individuals witha tool that can aid them in accomplishing instru-mental ADLs required in a kitchen environment. Thesystem can be integrated into an intelligent environ-ment or with other complementary systems such asthe Cook’s Collage and Archipel, where context-awaresensors placed in the kitchen such as cameras, LEDs,acoustic devices and RFID tags can be used to aid andmonitor an individual in additional meal preparationtasks or other related complex ADLs such as cooking,eating, and washing the dishes.

METHODSAssistive Kitchen System Design

The design of our initial prototype of theassistive kitchen system consists of two main sub-systems: (1) user interface, and (2) automated cabinet.An overview of the overall system is presented inFigure 1. This initial prototype has been designed withthe following specific aims: (1) to develop an easy touse interface to promote natural communications dur-ing kitchen tasks, and (2) design a cost-effective andeasy to use automated cabinet system using existing

Automated Cabinet

Micro controller

Speakers

Visual DisplayVisual Interface andSpeech Synthesizer

High-level Control

Databases

Internet

Speech Recognitionand Analysis

Microphone

FIGURE 1 System overview (color figure available online).

M. Ficocelli and G. Nejat 248

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

cabinet components and available off-the-shelf com-ponents. The prototype provides the perfect platformto obtain feedback regarding functionality, acceptance,and usability of such a system.

The assistive kitchen system prototype is initiatedthrough the detection of close-range sound or whenintentionally verbally prompted by a user. All requestsfrom users are verbal and are registered by the SpeechRecognition and Analysis module, and are also dis-played visually to the user for verification and recall viathe Visual Interface and Speech Synthesizer module.Three specific cases are identified by the system: (1) theuser wants to retrieve an item(s) from the kitchen,(2) the user wants a recipe to retrieve the items toprepare a meal, and/or (3) the user wants to store anitem(s).

The overall system consists of a database that storesthe names of available kitchen items and their locationswithin a cabinet. If the user is requesting to retrieveitems, the user interface then provides the user withthe location of a required item(s) within a correspond-ing cabinet. This information is provided to the userboth verbally through a speech synthesizer and non-verbally as text on the display. The interface can alsoprovide a list of stored items that the user can eas-ily choose from to retrieve. Once the location of theitem is determined, the automated cabinet sub-systemis used to bring the cabinet shelf that the item isstored on to an accessible ergonomic height for theuser. All shelves have the ability to translate horizon-tally out towards the user to provide easy reach for arequested item. A similar procedure is implementedwhen a user would like to place items on shelves inthe cabinet.

With respect to recipe finding, a high-level con-trol module looks up a specific recipe name for theuser. Two recipe-searching approaches are incorpo-rated: an internal database search and an online searchusing ehow-recipes (http://www.ehow.com/recipes/).If a recipe is not found in the database, the GoogleRSS (Really Simple Syndication) reader is utilized toextract RSS feed information from the eHow—Recipeswebsite. Once the recipe is found, the system can com-municate the items that are needed for the recipe to auser one at a time. The automated cabinet sub-systemruns simultaneously in order to help the user retrievethese items. The following sub-sections will discuss thedevelopment of the sub-systems and modules of theassistive kitchen system.

Speech Recognition andAnalysis Module

User speech is recognized via the SpeechRecognition and Analysis module. Recognition isperformed utilizing Julius, which is a two-pass largevocabulary continuous speech recognition (LVCSR)decoder (Lee & Kawahara, 2009). Words are recognizedbased on their phonemes and their approximate loca-tion in an utterance. Speech analysis then comparescorresponding synsets to its own database of words.The LVCSR software has been customized to sup-port the vocabulary, dialog and action-based contextneeded during the proposed kitchen activities. We haveincorporated the person independent VoXForge (2009)acoustic model into our module. This acoustic modelis composed of statistical representations, created viaHidden Markov Models, for each phoneme in theEnglish language to account for persons with differentaccents and speaking styles. The acoustic model hasbeen trained using 625 unique voices.

Visual Interface and SpeechSynthesizer Module

The Visual Interface and Speech Synthesizer Modulewas developed in a C++ software framework and isused to both visually display the status of the interac-tion as well as also provide verbal cues and promptsto the user. The visual display provides informationregarding the following parameters: (1) Mode: whichis used to indicate the activity at hand, that is, itemretrieval, (2) Item to Get: defines which item of inter-est that needs to be retrieved at a certain time, thatis, a can of chicken soup or a plate, (3) Recipe:Defines the recipe name for the meal preparationtask, (4) Items: Outlines all the items needed for therecipe, and (5) Cabinet shows on which of the threeshelves in the cabinet a particular item is located.In addition, the visual interface displays three moretextboxes which include the verbal request from theuser as recognized by the speech recognition mod-ule (User Input), the speech spoken by the system(System Output) and guides for answering the sys-tem’s questions (Answer Guide). The Answer Guideis used to provide users with options, including pro-viding activity/food options based on the time of theday. For example, in the morning, the system mayask what the user would like to eat for breakfast and

249 Design of an Interactive Assistive Kitchen System

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

(a)

(b)

Item Retrieval

Plate

I would like a plate

System

User Input

Answer Guide

Okay, let’s get a PLATE

Item Retrieval

Plate

I would like a plate

System

User Input

Answer Guide

FIGURE 2 Visual display (color figure available online).

the Answer Guide could provide food options such ascereal, bread, and so forth. This information, similarto the other parameters, is also verbally presented tothe user via the speech synthesizer in addition to beingdisplayed in the textbox under the heading AnswerGuide.

An example scenario using the Visual Display isshown in Figure 2. In particular, a user tells the sys-tem that he/she would like a plate, the system’s Modeparameter indicates the item retrieval sub-task and theItem to Get parameter states that the item of interest isa plate. The system confirms this action and identifiesthat this item is on the bottom shelf (i.e., shelf #3).

Automated CabinetThe automated cabinet requires that adjustments be

made directly to an existing kitchen cabinet in orderfor all three shelves to be automated one at a time toan accessible height. The cabinet can be placed at aheight at which the bottom shelf is within the optimumreach envelope of the user. The top two shelves havealso been designed to translate vertically downwards toan acceptable height within this reach envelope usinga lifting mechanism. Each shelf will de-couple fromthe shelf supports and lock into the lifting mechanism.At the required height, all shelves have the ability totranslate horizontally out towards the user to provideeasy reach for a requested item. Figure 3 illustrates thesteps utilized to bring the top shelf of the automatedcabinet to an acceptable height.

The overall movement of each shelf is controlledby three major elements which are the ‘shelf rollermechanism’ that rolls the shelf horizontally in andout, the ‘lifting mechanism’ used to raise/lower a shelfas needed, and the ‘coupling and de-coupling mech-anism’ used to couple/de-couple a shelf with respectto the shelf supports and also lock/disengage the shelfto/from the lifting mechanism. One of the main designcriteria is to ensure that all the components needed forthis application can fit within the cabinet space.

The shelf roller mechanism

In order to provide the horizontal translationmotion of all three shelves, a DC motor driven rollersystem is designed to be placed underneath each shelf.Namely, a shelf roller mechanism consisting of a motordriven roller can move the shelf horizontally in bothdirections. To aid the motion of the shelf, four free-rolling rollers are distributed along the width of theshelf and placed at the same height as the driving

(a) (b) (c)

FIGURE 3 (a) Lifting arm raised to required shelf position, (b) shelf de-coupled into lifting arm, and (c) desired shelf lowered to anacceptable height (color figure available online).

M. Ficocelli and G. Nejat 250

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

roller to assist the horizontal motion by minimizingfriction and keeping the shelf in a stable configura-tion. The advantage of this actuation system is that itis compact, cost-effective and can be placed directlyunderneath each shelf. In order to design an appro-priate motorized roller system, the minimum motorpower (in watts) required to move an individual shelfwith various kitchen items placed on top of it needs tobe determined:

Pmr =[

WL367D

(2k + μr) + nwμdv × 103

102D

]1η

+ Fpv,

(1)

where W is the combined weight of the items on theshelf and the shelf itself, L is the total length of allthe rollers, and D is the roller diameter; k is the rollingfriction factor (in meters), μ is the coefficient of fric-tion at the roller shaft and the bearing interface, and ris the roller journal radius (d is the journal diameter);n is the number of rollers supporting the total weightof the shelf and items, w is the weight of the rotat-ing part of each roller, v is the linear velocity of theshelf moving across the rollers, and η is the efficiencyof the drive system. Lastly, Fp is the resistive forces inthe free-rolling rollers that must be overcome by themotor driven roller:

Fp = F1 + F2 + F3, (2)

where,

F1 = WkR

, F2 = (W + wn)μrR

, F3 = nwv2

gL.

F1 is the resistance to rolling of the shelf on the free-rolling rollers, F2 is the frictional resistance in thefree-rolling rollers’ bearings, F3 is the resistance due tosliding of the shelf on the free-rolling rollers and theforce required to impart kinetic energy to those roller.R is the roller radius and g is gravity.

Shelf coupling and de-couplingmechanism

In order to lower the top two shelves and bringforward the bottom shelf; each shelf will need tode-couple from the shelf supports and lock into thelifting mechanism. To achieve this, two locking ridersare placed on the lifting arm, one at each end. Each

shelf has machined tapered edges in order to easilyslide into the tapered openings in the locking riders.Once the shelf has rolled into the riders, the riders thenstart moving outwards until the shelf is completelyde-coupled from the shelf supports. When the shelf iscommanded to be inserted back to its original position,the locking riders will start to move in the oppositedirection until the driving roller from the shelf rollermechanism makes contact with the shelf. The motortorque required to move the shelf during coupling anddecoupling is:

Tls = Fp + Ffr

2πPsnls, (3)

where Ffr is the friction forces internal to the leadscrewmechanism, Fp is the resistive forces encountered whenmoving the shelf into and out of the riders, Ps is theleadscrew pitch, and ηls is the leadscrew efficiency. Ffr

can be defined as:

Ffr = μls W cos(γ ), (4)

where γ = 0◦ for horizontal motion and μls is thecoefficient of friction in the leadscrew mechanism.Alternatively, Fp can be defined as:

Fp = μw W , (5)

where μw is the coefficient of sliding friction. The min-imum power rating, in watts, for an appropriate motorcan be found using:

pls = Tlsωls, (6)

where ωls is the angular velocity of the leadscrew, whichcan be found from the required linear velocity, vls, ofthe shelf, that is, ωls = 2πpls vls. Herein, pls is the pitchof the thread in the leadscrew defined in rev/m (rev/ft).

Lifting mechanism

A lead-screw-based linear track actuator is used totranslate vertically and individually the top two shelvesto an acceptable reach range (bottom shelf’s height).A lifting arm can be connected to the linear track actu-ator on one side and a guide mechanism on the otherside. For translation of the shelf, the lifting arm muststay parallel to the shelf supports with minimal deflec-tion. A pulley system ensures the arm is straight and

251 Design of an Interactive Assistive Kitchen System

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

two free rolling bearings in the guide system restrictthe motion of the arm to the vertical axis. In order todetermine the minimum required motor power, firstthe motor torque required to lift the shelf vertically isdetermined:

Tla = Fg + Ffr

2πPsnls, (7)

where the force due to gravity is Fg = W sin γ , andγ is 90◦ for vertical motion. Ffr consists of the slidingfriction forces of the guide and pulley system. The min-imum power rating, in watts, for an appropriate motorcan then be determined to be:

Pla = Tlaωls, (8)

where ωls can be found from the required linear verticalvelocity of the shelf.

The minimum required power for the motors of allthree systems are multiplied by a 1.5 safety factor.

High-Level Control ArchitectureWe utilize a finite-state machine (FSM) approach

to design the high-level controller for the assistivekitchen system. The FSM is a mathematical abstrac-tion consisting of a set of states and actions whichmatch the system’s output behavior to a given userinput. The FSM for the assistive kitchen system is

composed of eight states, Figure 4(a). Each FSM actionrepresents a set of actions performed by the systemin order to achieve a specific state. The FSM initi-ates from the Standby state. An input command isprovided from the Speech Recognition and Analysismodule to retrieve/store an item or find a recipe. TheEnter Search action is then performed to achieve theSearch state. Since the FSM we utilized was devel-oped using a heterogeneous design approach, it allowsfor a hierarchy in the FSM design. In particular, theSearch state is refined into logical sub-states forminga sub-FSM as shown in Figure 4(b). Once the Searchstate is entered, the sub-FSM initiates from its ownStandby state. From this state, the system can per-form an item location search or a recipe search usingthe corresponding database or also the online optionfor the latter. For example, it can move to the SearchRecipe Database State via the Search for Stored Recipeaction. If the recipe is found in the database, thesub-FSM returns to its Standby state via the Returnaction. The Return action sends the recipe items tothe Visual Interface and Speech Synthesizer moduleto display and verbally state to the user. If the recipeis not in the recipe database, the sub-FSM moves tothe Search Internet for Recipe state via the Searchfor On-line Recipe action. Within this state, the RSSreader is used to obtain the corresponding recipe fromthe internet. Once the recipe is found, the sub-FSMreturns to its Standby state via the Return action, whilealso sending the recipe items to the Visual Interface

Item received

Shelf #2down

Shelf #2up

Shelf #1down

Shelf #1up

Shelf #3out

Shelf #3in

Enter search

Item on Shelf #2

Item received

Item received

Item onShelf #1

Item onShelf #3

Fault

Shelf #1returned

Shelf #2 returned

Shelf #3 returned

Fault Fault

Fault

Standby

Search

Fault

Fault

Fault Search for

Item

Standby

SearchShelves

Database

Search Recipe Database

Return ShelfNumber

Search forStoredRecipe

Return

Search Internet for Recipe Search for

On-lineRecipe

Return

(a) (b)

FIGURE 4 (a) FSM for the Assistive Kitchen System, and (b) sub-FSM for the Search state.

M. Ficocelli and G. Nejat 252

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

and Speech Synthesizer module. The sub-FSM is alsoutilized to identify the location of items via the SearchShelves Database state. It enters this state using theSearch for Item action. Within this state, a search algo-rithm is used to find the corresponding shelf the itemis stored on. Once an item’s location is found, theReturn Shelf Number action returns the sub-FSM tothe Standby state and sends this shelf number to theVisual Interface and Speech Synthesizer module tocommunicate to the user. The master FSM can thenlower the appropriate shelf to allow the user to retrievethe item by using the corresponding Item on Shelfaction. For example, if the item is located on shelf#2 (middle shelf), the Item on Shelf #2 action is per-formed and the system enters the Shelf #2 Down statein which the appropriate signal is sent to the micro-processor to move this shelf from its position in thecabinet into the reach envelope of the user. When thesystem has confirmed that the user has removed therequested item from the shelf, the system performs theItem Received action to move Shelf #2 back to itsoriginal position via the Shelf #2 Up state, in whichthe corresponding signal is sent to the microprocessorto move the shelf up and back into its original posi-tion in the cabinet. The FSM then performs the Shelf#2 returned action and moves the FSM back to theStandby state, where it waits for the next input. Similaractions and states exist for shelves #1 (top shelf) and#3 (bottom shelf). If the search request was to find arecipe, once the items in the recipe have been found,the FSM sequentially repeats the aforementioned pro-cedure to retrieve all the necessary items. It should benoted that if there is any fault detected when movingthe shelves of the cabinet via the onboard sensors, theFSM will move back to its Standby state using the Faultaction. Once the Fault is cleared, the FSM moves backto its previous state via the same path and continues itsprevious actions.

Automated Cabinet PrototypeDevelopment

Based on the aforementioned design, we have devel-oped a physical prototype of the cabinet, Figure 5.The specifications of this cabinet are presented inTable 1. Based on the specifications in Table 1 and themotor requirements in Equations (1)–(8), the motorspresented in Table 2 were chosen for the automatedcabinet.

FIGURE 5 Overview of automated cabinet system (color figureavailable online).

TABLE 1 Cabinet specifications

Cabinet height 77 cm (30.3 inches)

Cabinet width 76 cm (29.9 inches)Shelf length 28 cm (11 inches)Shelf width 56 cm (22 inches)Mass of shelf 2.27 kg (5 lbs)Shelf load capacity 11.4 kg (25 lbs)Maximum shelf

travelling speed3cm/s (1.18 inches/s)

TABLE 2 Motor selection

Mechanism MotorPower

output (W)

The shelf rollermechanism

ZHENGKE ZGA 42 RH 5

Shelf coupling andde-couplingmechanism

ZHENGKE ZGA 42 RH 5

Lifting mechanism Firgelli AutomationsFA-200-TR-24(Linear Actuator)

13

As previously mentioned, the user will be able to askfor kitchen items already stored on the shelves of thecabinet through the Speech Recognition and Analysismodule. The item retrieval and storage search will lookthrough its database of stored items to identify theitem and its location. Once the location of the itemis known, it will send a signal to the microcontrollerin order to lower and/or move forward the specifiedshelf on which the item sits. During this time theuser will also be provided with information about theactions taken by the overall system through the VisualInterface. When an item is placed onto the shelf, theshelf is moved back to its initial location.

253 Design of an Interactive Assistive Kitchen System

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

PROTOTYPE TESTING PROTOCOLPreliminary experiments were conducted to evalu-

ate the performance of the overall proposed assistivekitchen system. An interaction scenario between par-ticipants and the kitchen system was developed, whereeach participant asked the system to locate an item,retrieve that item, and then restore the item. This listincluded common items that potentially can be foundon kitchen shelves such as cans of soup and tuna, teaboxes, small cereal boxes and cracker boxes. The cabi-net was placed approximately 137 cm (54 inches) fromthe ground, and the laptop controlling the system anddisplaying the interface was placed on a table near thecabinet (as shown in Figure 5). The height of the cabi-net was chosen to reflect the average floor-to-bottomof cabinet height of wall kitchen cabinets in NorthAmerica. The food items were distributed on the threeshelves. The shelves were lowered and brought forwardat a height of approximately 142 cm (56 inches) fromthe floor. Fifteen healthy participants (10 within theages of 20–35, and 5e within the ages of 56–68) tookpart in the experiments (mean = 38.13; std. dev. =17.75). Six of the participants were females (three ofwhom were from the older cohort) and nine were males(two of whom were from the older cohort). None ofthe participants had any prior experience with assistivetechnologies for kitchen environments. All participantscould speak English, however, for four of the par-ticipants, English was not their first language. Theparticipants were given a tutorial on how the systemoperates prior to testing. Each participant interactedwith the system a total of five times.

A detailed analysis was conducted on the per-formance of the Speech Recognition and AnalysisModule, Visual Interface Module and AutomatedCabinet. In addition to the performance experiments,acceptance of the interactive system by elderly userswas also measured via a questionnaire. In particular, amodified version of the Unified Theory of Acceptanceand Use of Technology (UTAUT) scale (Venkatesh,Morris, Davis, & Davis, 2003) was provided to the fiveolder participants to complete after their interactionswere finished.

The UTAUT combines eight previous models oftechnology acceptance into one model incorporat-ing measurable factors such as Behavioral Intention,Anxiety, and Attitude. The UTAUT was first developedto measure technology acceptance and predict usage in

the workplace. However, it has been designed so that itcan be adapted to any technology of interest. For exam-ple, Heerink, Krosë, Wielinga, and Evers (2009) revisedthe model to measure users’ acceptance of assistiverobots. This included adding additional new constructssuch as Trust and Perceived Adaptability as well asincorporating the Perceived Ease of Use and PerceivedUsefulness constructs from the Technology AcceptanceModel (TAM) (Davis, 1989). These additional con-structs haven been shown to be important constructsfor users of assistive technology. The model was testedwith elderly participants and the assistive robot iCatin a long-term care facility. In our own study, eight ofthe revised UTAUT constructs (for a total of 24 ques-tions) which we found to be directly applicable to thequality of life of elderly users were used to measure theacceptance and use of the assistive kitchen system on a5-point Likert scale ranging from 1 (not at all) to 5 (verymuch). The constructs and corresponding questions arepresented in Table 3.

RESULTS AND DISCUSSIONSPreliminary Performance Testing

Results of the system performance experiments arepresented in Table 4. It can be seen that the system wassuccessful at selecting and executing the appropriatebehaviors throughout the interactions with the partici-pants. The number of trials represents the total numberof opportunities that existed for each of the behaviorsof the system.

The acoustic model we utilized for speech recog-nition was not trained to be participant-dependentand thus, inherently, as a general limitation to per-son independent speech recognition techniques, it mayexperience difficulty correctly recognizing differentpronunciations of the same words. This was evident inthe achieved success rate of 93% amongst the 15 par-ticipants. In particular, the six failures are a result ofthe system not being able to correctly recognize cer-tain words spoken by two male non-native Englishspeakers, one from the older cohort and one from theyounger cohort. Our findings are consistent with previ-ous research that has found that English speech recog-nition systems have more trouble recognizing wordsspoken by males than females (Goldwater, Jurafsky, &Manning, 2010). The two words spoken by these twoparticipants that were the most difficult for the system

M. Ficocelli and G. Nejat 254

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

TABLE 3 Modified UTAUT constructs

Anxiety (ANX)∗:1. When using the kitchen system, I am afraid to make

mistakes with it2. When using the kitchen system, I am afraid to break

something3. I find the kitchen system scary4. I find the kitchen system intimidating

Attitude towards using the system (ATT):5. I think it’s a good idea to use the kitchen system6. The kitchen system would make my life more

interesting7. It’s good to make use of the kitchen system

Facilitating Conditions (FC):8. I have everything I need to make good use of the

system9. I know enough of the system to make good use of it

Behavioral Intention to use the system (BI):10. I think I’ll use the kitchen system during the next few

months11. I am certain to use the kitchen system during the next

few months12. I’m planning to use the kitchen system during the next

few months

Perceived Adaptability (PA):13. I think the kitchen system can be adaptive to what I

need14. I think the kitchen system will only do what I need at

that particular moment15. I think the kitchen system will help me when I consider

it to be necessary

Perceived Ease of Use (PEU):16. I think I will know quickly how to use the kitchen

system17. I find the kitchen system easy to use18. I think I can use the kitchen system without any help19. I think I can use the kitchen system when there is

someone around to help me20. I think I can use the kitchen system when I have a

good manual

Perceived Usefulness (PU):21. I think the kitchen system is useful to me22. It would be convenient for me to have the kitchen

system

Trust (TU):23. I would trust the instructions of the kitchen

system24. I would follow the instructions the kitchen system

gives me

∗Scores on negative questions such as for Anxiety have reverse scores,where a stronger agreement leads to a lower score.

TABLE 4 System performance results

Expected systembehavior

No. oftrials

No. offailures

Successrate

Recognize speech input 80 6 93%Displays item location 75 0 100%Rolls shelf out/in 150 0 100%De-couples/couples shelf

(on the first try)150 7 95%

Lifts/lowers shelf 150 0 100%

to recognize were “want” and “tea.” Even though 93%is a high success rate, we would like to see success ratesof 100% for our particular application. To address thislimitation for our future work, we have been focusingon the utilization of acoustic models that are opti-mized specifically for older adults (Anderson et al.,1999). Furthermore, if the users are known in advance,which is true for personal home settings, we can alsotrain the speech recognition system for the identifiedusers.

The main mechanical issue that was noted duringtesting was that the shelf’s tapered edges sometimesfailed to completely slide into the locking riders, mak-ing it difficult during these instances to reliably decou-ple the shelf from the shelf supports. Namely, as thelocking riders started to move away from the cabinetto de-couple a shelf, the shelf would not move therequired distance in order to de-couple from the shelfsupports. This scenario occurred in 7 out of the 150 tri-als on the system’s first try at de-coupling the shelf.However, the system was able to de-couple the shelfeither on the second or third try. Although de-couplingwas achieved on subsequent tries by the system, thisissue is being addressed by installing electromagnets onthe locking riders and corresponding metal strips onthe sides of the shelves. These electromagnets can thenbe energized only during coupling/de-coupling of theshelves.

Once the participants were finished interacting withthe system, they were each asked if there were any otherfeatures they would like to see incorporated into thesystem. Sixty-seven percent of the participants statedthat pictures of available items and/or video clipsof various meal preparation activities could also beincluded in the visual display.

The current initial prototype allowed us to test ourconceptual design focusing on such aspects as speechrecognition, visual interface and the mechanical designof the automated cabinet for accessibility. We are in

255 Design of an Interactive Assistive Kitchen System

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

the process of adding additional sensors to individ-ual shelves for directly monitoring a particular item’splacement or retrieval off of a shelf. This will help usupdate the database as needed as well as monitor thatitems are properly placed on corresponding shelves.Each shelf can be divided into grids and force sensorscan be used for each grid in order to detect a changein weight locally on the shelf as well as in the totalweight of the shelf to determine if items have beenplaced onto or retrieved from the shelf. Cameras andfeature recognition algorithms can also be used to visu-ally identify a particular item on a shelf and its exactlocation. Long-term use items such as plates, cups andutensils can have RFID tags placed on them in order toidentify their exact locations. For our initial prototype,the system had asked a user to confirm that an itemhad been removed from or placed onto a shelf.

As our proposed automated cabinet has beendesigned to be incorporated within an original fixedframe of a standard cabinet, it can be integrated intoa number of cabinets in the kitchen and controlled bythe same high-level controller. The user interface canbe updated to present the information not only of theshelf that an item is on but also the appropriate cabinetor drawer based on an updated database which storesthe names of available kitchen items, their locationsin the kitchen as well as within a respective cabinetor drawer. In order to direct a person to a particularcabinet or drawer of interest in the kitchen, context-aware sensors can be used. For example, light/LEDsensors can be affixed to the outside of cabinets ordrawers and light up or blink when a particular itemof interest is in these locations. Our automated cab-inet system can then bring the appropriate shelf theitem is on within the reach envelope of the person.We can also automate drawers to slide out along theirguides when an item of interest is in them. If a kitchenconsists of a combination of both automated and stan-dard cabinets and drawers, for the standard cabinetsand drawers, we can still incorporate context-aware sen-sors to aid users to identify the appropriate cabinetor drawer location for a particular item. The systemcan also prompt a user to obtain an item from a par-ticular shelf in a standard cabinet, however, the shelfitself will not be automated. In addition to cabinetsand drawers, the kitchen also includes storage appli-ances such as a refrigerator and a freezer. To date, thereare refrigerators that are being manufactured that havemanually sliding shelves, which could potentially also

be automated. Furthermore, sensors could be placedat the different shelf locations in the refrigerator andfreezer to also guide the user to an appropriate shelf onwhich a particular item is on. In addition to optimizingthe internal modules of the system, the overall systemcan be integrated within an intelligent environment,where environmental sensors placed in the kitchen canbe used along with the proposed system to aid andmonitor an individual in sequential ADLs related tomeal preparation, cooking, eating and cleaning up.

Modified UTAUTThe modified UTAUT questionnaire was completed

by all five older participants (mean = 61.40; std. dev. =5.13). Cronbach’s alpha (Santos, 1999) was determinedfor each of the constructs in order to verify inter-reliability between the questions for the participantgroup. The alpha values are presented in Table 5.In general, an alpha greater than 0.7 is consideredto be acceptable for this type of study (Nunnally &Bernstein, 1978). From Table 5 we can see that thealpha value for trust is the only one below 0.7. This canbe a result of the small number of questions (i.e., 2) forthis particular construct as well as the speech recogni-tion results. There were two instances for this particulargroup that the speech recognition and analysis mod-ule was unable to register the particular item the userwanted.

The descriptive statistics for the individual questionsof the modified UTAUT scale are presented in Table 6.Based on the results, it is worth noting that, overall, theparticipants found the assistive kitchen system to beuseful and easy to use on their own. Furthermore, theyalso experienced little anxiety towards it. In particular,they were not intimidated or afraid of using the new

TABLE 5 Cronbach’s alphafor constructs

Modified UTAUTconstruct Alpha

ANX 0.78ATT 0.95FC 0.77BI 0.85PA 0.79PEU 0.71PU 0.89TU 0.63

M. Ficocelli and G. Nejat 256

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

TABLE 6 Descriptive statistics for modified UTAUT results

Question # Min Max Mean Std. dev.

1 3 4 3.6 0.542 3 5 4.2 0.833 4 5 4.6 0.554 3 5 4.2 0.835 3 4 3.4 0.546 3 4 3.4 0.547 3 5 3.6 0.898 4 5 4.4 0.549 3 4 4 0.7

10 2 4 3.4 0.8911 2 5 3.4 1.1412 3 5 4.2 0.8313 3 5 3.8 0.8314 3 5 4.2 0.8315 3 5 4 0.7016 3 4 3.8 0.4417 3 5 4 0.7018 3 5 4.2 0.8319 3 5 4 120 3 5 4.2 0.8321 3 5 4.2 0.8322 4 5 4.4 0.5423 3 5 4 124 2 5 3.8 1.09

TABLE 7 Correlation

Independentvariable

Dependentvariable

Pearsoncorrelationcoefficient

Sig.(2-tailed)

ANX PU −0.75 0.146ATT BI 0.6 0.281FC BI 0.6 0.282PEU BI 0.84 0.078PU BI 0.89 0.040PA PU −0.49 0.402

system. One of the important indicators of the mod-ified UTAUT scale is the behavioral intention to usethe system again in the near future. The results presenta high level of interest in terms of planning to use thesystem in the next few months (mean = 4.2, std. dev. =0.83).

Table 7 presents correlation results between con-structs of the modified UTAUT scale. Significancetesting was conducted using an alpha = 0.05. It wasfound that a positive significant relationship existsbetween perceived usefulness of the system and behav-ioral intention to use the system. This relationshiphighlights the importance of this group being able to

identify the advantages of the assistive kitchen systemduring the initial short interactions in order for themto want to use the system again in the future.

CONCLUSIONIn this paper, we present the design of an assistive

kitchen system to assist elderly individuals with cogni-tive impairments to complete ADLs such as retrievingand storing items, and obtaining recipes for mealpreparation. An initial prototype was developed con-sisting of a user interface and automated cabinet totest the functionality and feasibility of the proposeddesign. In addition, a modified UTAUT scale was usedto measure acceptance and potential use of the pro-posed system by a group of older adults. The resultsfrom the modified UTAUT, though only focusing on asmall sample of older adults, show promise for the useof the system for the outlined kitchen ADLs, and moti-vate further development and testing of the proposedsystem for the intended population. Our future workwill consist of optimizing and adding additional func-tionalities to the prototype in order to conduct largescale studies with user group participants.

REFERENCESAnderson, S., Liberman, N., Bernstein, E., Foster, S., Cate, E., Levin, B., &

Hudsin, R. (1999) Recognition of elderly speech and voice-driven doc-ument retrieval. In Proceedings of the IEEE International Conferenceon Acoustics, Speech, and Signal Processing (pp. 145–148), Pheonix,AZ.

Asada, H. H., Shaltis, P., Reisner, A., Rhee, S., & Hutchinson, R. C.(May/June 2003). Mobile monitoring with wearable photoplethys-mographic biosensors. IEEE Engineering in Medicine and BiologyMagazine, 28–40.

Asfour, T., Regenstein, K., Azad, P., Schroder, J., Bierbaum, A.,Vahrenkamp, N., & Dillmann, R. (2006). ARMAR-III: An IntegratedHumanoid Platform for Sensory-Motor Control. In the Proceedingsof IEEE/RAS International Conference on Humanoid Robots (pp.169–175). Genova, Italy.

Beetz, M., Stulp, F., Radig, B., Bandouch, J., Blodow, N., & Dolha,M. (2008). The Assistive Kitchen—A Demonstration Scenario forCognitive Technical Systems. In the Proceedings of IEEE InternationalSymposium on Robot and Human Interactive Communication (pp.1–8). Munich, Germany.

Chan, J., Nejat, G., & Chen, J. (2011). Designing intelligent sociallyassistive robots as effective tools for cognitive interventions.International Journal of Humanoid Robotics, 8(1), 103–126.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, anduser acceptance of information technology. MIS Quarterly, 13(3),319–339.

DIAGO 504 Adjustable Height Cabinet. Reliable Independent LivingServices. Retrieved on April 3, 2010 from www.reliableliving.com.

Dobriansky, P. J., Suzman, R. M., & Hodes, R. J. (2007). WhyPopulation Aging Matters—A Global Perspective, National Instituteon Aging and U.S. Department of Health and Human Services.

257 Design of an Interactive Assistive Kitchen System

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014

Retrieved July 1, 2019, http://www.nia.nih.gov/researchinformation/extramuralprograms/behavioralandsocialresearch/globalaging

eHow Recipes. Demand Media, Inc. Retrieved May 24, 2011 from http://www.ehow.com/recipes/

Giroux, S., Bauchet, J., Pigot, H., Lussier-Desrochers, D., & Lachappelle,Y. (2008). Pervasive behavior tracking for cognitive assistance. InProceedings of the International Conference on PErvasive Technolo-gies Related to Assistive Environments (pp. 1–7). Arlington, TX.

Goldwater, S., Jurafsky, D., & Manning, C. D. (2010). Which wordsare hard to recognize? Prosodic, lexical, and disfluency factors thatincrease speech recognition error rates. Speech Communication, 52,181–200.

Grindle, G. G., Wang, H., Salatin, B. A., Vazquez J. J., & Cooper, R.A. (2011). Design and development of the personal mobility andmanipulation appliance. Assistive Technology, 23, 81–92.

Heerink, M., Kröse, B. J. A., Wielinga, B. J,. & Evers, V. (2009) Measuringacceptance of an assistive social robot: a suggested toolkit. InProceedings of IEEE International Symposium on Robot and HumanInteractive Communication (pp. 528–533), Toyama, Japan.

Kinsella, K., & Velkolt, V. A. (2001). An Aging World—2001. U.S Depar-tment of Health and Human Services and U.S Census Bureau Report.

Korhonen, I., Parkka, J., & Van Gils, M. (May/June 2003). Health mon-itoring in the home of the future. IEEE Engineering in Medicine andBiology Magazine, 66–73.

Lawton, M. P., & Brody, E. M. (1969). Assessment of older peo-ple: Self-maintaining and instrumental activities of daily living. TheGerontologist, 9, 179–186.

Lee, A., & Kawahara, T. (2009). Recent development of open-source speech recognition engine Julius. In Asia-Pacific Signal andInformation Processing Association Annual Summit (pp. 131–137).Sapporo, Japan.

Lesser, V., Atighetchi, M., Benyo, B., Horling, B., Raja, A., Vincent, R.,Wagner, T., Xuan, P., & Zhang, S. X. Q. (1999). The intelligent hometestbed. In Proceedings of Autonomy Control Software Workshop(pp. 1–8), Seattle, WA.

Mahoney, D., Mahoney, E., & Liss, E. (2009) Outcomes from Aging in Placewith AT EASE Automated Technology for Elder Assessment, Safety,and Environmental Monitoring. Gerontechnology, 8(1), 11–25.

Mahoney, D., Mutchler, P., Tarlow, B., & Liss, E. (2008). Real worldimplementation lessons and outcomes from the worker interactivenetworking (WIN) project: Workplace based online caregiver supportand remote monitoring of elders at home. Telemedicine and e-Health,14(3), 224–234.

McColl, D., Chan, J., & Nejat, G. (2012). A socially assistive robot for meal-time cognitive interventions. Journal of Medical Devices—Transactionsof the ASME, 6(1), 017559.

Mihailidis, A., Boger, J., Craig, T., & Hoey, J. (2008). The COACH prompt-ing system to assist older adults with dementia through handwashing:An efficacy study. BMC Geriatrics, 8(28).

Nejat, G., & Ficocelli, M. (2008). Can I be of assistance? The intelligencebehind an assistive robot. IEEE International Conference on Roboticsand Automation (pp. 3564–3569), Pasadena, CA.

Nunnally, J. C., & Bernstein, I. H. (1978). Psychometric theory: McGraw-Hill, New York.

Park, S., & Jayaraman, S. (May/June 2003). Enhancing the quality oflife through wearable technology. IEEE Engineering in Medicine andBiology Magazine, 41–48.

Rantz, M. J., Marek, K. D., Aud, M., Tyrer, H. W., Skubic, M., Demiris, G.,& Hussam, A. (2006). A technology and nursing collaboration to helpolder adults age in place. Nursing Outlook, 53(1), 40–45.

Reisberg, B., Ferris, S. H., de Leon, M. J., & Crook, T. (1982).The global deterioration scale for assessment of primarydegenerative dementia. American Journal of Psychiatry, 139,1136–1139.

Rogers, W. A., Meyer, B., Walker, N., & Fisk, A. D. (1998). Functionallimitations to daily living tasks in the aged: A focus group analysis.Human Factors, 40(1), 111–125.

Santos, J. R. A. (1999). Cronbach’s alpha: A tool for assessing thereliability of scales. Journal of Extension, 37, 1–5.

Tatemichi, T. K., Desmond, D. W., Stern, Y., Paik, M., Sano, M., & BagiellaE. (1994). Cognitive impairment after stroke: Frequency, patterns, andrelationship to functional abilities. Journal of Neurology, Neurosurgery& Psychiatry, 57, 202–207.

Tierney, M. J., Tamada, J. A., Potts, R. O., Jovanovic, L., & Garg, S.(2001). Clinical evaluation of the GlucoWatch biographer: A continualnon-invasive glucose monitor for patients with diabetes, Biosensors &Bioelectronics, 16, 621–629.

Tran, Q. T., Calcaterra, G., & Mynatt, E. D. (2005). Cook’s Collage: Déjàvu Display for a Home Kitchen. In Proceedings of Home OrientedInformatics and Telematics. York, UK.

Venkatesh, V., Morris, M. G., Davis, F. D., & Davis, G. B. (2003). Useracceptance of information technology: Toward a unified view. MISQuarterly, 27, 425–478.

VERTI Adjustable Height Shelving Reliable Independent Living Services.Retrieved on April 3, 2010 from www.reliableliving.com.

Visual Assistant. (2011). AbleLink Technologies, Inc. Retrieved June 20,2010 from www.ablelinktech.com

VoxForge Acoustic Models. (2009). VoxForge. Retrieved December 17,2010 from http://www.voxforge.org/home/downloads

Yamazaki, T. (2006). Beyond the smart home. In Proceedings of theInternational Conference on Hybrid Information Technology (pp.350–355). Jeju Island, Korea.

M. Ficocelli and G. Nejat 258

Dow

nloa

ded

by [

Cas

e W

este

rn R

eser

ve U

nive

rsity

] at

17:

26 0

4 N

ovem

ber

2014